Telehealth and eHealth

By improving accessibility, efficiency, and accuracy, emerging diagnostics and teledentistry are enhancing dental care and other branches of healthcare as well. This article examines how remote consultations and AI-based diagnostics facilitate teledentistry, thereby reducing oral healthcare disparities in disadvantaged communities. By utilizing this approach to enhance early disease detection and treatment planning, extremely accurate diagnosis techniques improve patient outcomes by reducing the requirement for invasive treatments. Teledentistry and Intelligent Diagnostic Devices enable dental care to be more proactive and patient-focused as technology advances.

Healthcare modernization occurs through improved patient outcomes because primary care electronic health records integrate Artificial Intelligence data analysis with computer science. When automated systems collaborate with treatment optimization through superior diagnostics and streamlined administrative tasks physicians gain better efficiency levels. This study demonstrates how predictive analytics as well as big data management systems strengthened by algorithmic choice procedures make primary care functions more efficient. Research published in the latest scientific journal focused on AI implementations within Dean's Electronic health records should incorporate multiple essential steps for form verifications and dynamic analytical systems. The research shows that physician diseases detection becomes more effective with AI technology since the system identifies conditions earlier combined with upgraded clinical support features and personalized care planning for superior patient medical outcomes. Successful wide-scale AI implementation faces major hurdles since privacy concerns against data protection join forces with discrimination through AI programming in addition to difficulties with system implementation. Primary care operations will undergo transformation according to the assessment through deep learning algorithms that work alongside real-time information processing systems for healthcare issue prevention. This paper investigates the responsible implementation of AI in healthcare through a study of ethical requirements together with regulatory mandates and prospective research approaches. Electronic health record systems used in primary care operations will gain major advantages from combined applications of artificial intelligence data analytics and computer science methods. Medical professionals can attain superior patient results by integrating contemporary digital solutions with current challenge solutions to make diagnosis more precise and efficient and deliver personalized datadriven care.

Associated with COVID-19 and other emerging infectious diseases is the unprecedented blow, which demands a
return to a robust and adaptive approach to pandemic preparedness. Conventional epidemiological models are
extremely useful but have been found to be inadequate in processing the significantly increased volume, velocity,
and diversity of modern health data, thus limiting their ability to predict and respond effectively. Artificial
Intelligence (AI) as a technology has emerged and can fill these gaps by employing highly sophisticated data
analytics on multifaceted, multi-source data. Machine learning models, deep learning models, and natural
language processing techniques enhance outbreak forecasting, facilitate real-time disease monitoring, and
technical machine learning models, deep learning models, and natural language processing techniques optimize
public health decision-making. Specifically, the combination of clinical information, genomic sequences, patterns
of mobility, and social media signals has been used to enhance early warning systems and epidemiological
modeling. This manuscript is a critical piece on the use of AI to enhance preparedness for pandemics, with a focus
on predictive analytics, automated surveillance systems, and smart distribution tools for medical systems. It also
raises ethical and technical issues, such as data privacy, algorithmic explainability, and the global availability of
AI-empowered technologies. This paper demonstrates how AI-enhanced data analytics can transform
epidemiology into a more proactive, detailed, and collaborative field, and how data analytics tools and capabilities
will shape the present and future of epidemiology. Based on the findings, it is recommended that the use of AI in
pandemic preparation systems will significantly enhance resilience and reduce response time, thereby protecting
the health of people in future global health emergencies.

Artificial intelligence (AI) is poised to transform critical care by enhancing clinical decision-making, predictive accuracy, and operational efficiency. This editorial explores the expanding role of AI in intensive care units (ICUs), highlighting emerging applications such as predictive analytics, diagnostic imaging, realtime monitoring, and clinical decision support systems. Alongside these advances, the integration of AI presents critical challenges related to ethical implementation, regulatory oversight, clinician trust, and data interoperability. Drawing from current case studies and healthcare trends, this perspective underscores AI's potential to improve patient outcomes and optimize resource utilization. However, without rigorous validation, transparent practices, and a firm commitment to patient-centered design, AI risks becoming a liability rather than an asset. Sustainable adoption will require interdisciplinary collaboration, continuous evaluation, and the preservation of human connection at the heart of technologically supported care.

Background The health-related Sustainable Development Goals (SDGs), particularly SDG 3 have welcomed the introduction of technology into healthcare delivery, desalinating the accessibility to healthcare delivery. With the recent outbreak of the COVID-19, telehealth services have been the preferred means of service delivery to a wider population in settings where the physician-to-patient ratio is low. The study's objective is to investigate the principles, trends and challenges of using telehealth services for acute disease management in some hospitals within the Greater Accra region of Ghana. Methods A cross-sectional, descriptive quantitative study was conducted among healthcare professionals across four government health facilities in the Greater Accra Region:

Introduction: Telehealth is revolutionizing healthcare, particularly in post-operative care accessibility. However, technological limitations, costs, and communication barriers hinder its full implementation. This study examines healthcare providers' and patients' perception on telehealth services adoption for post-operative follow-ups at Korle Bu Teaching Hospital (KBTH), Ghana. Methodology: A descriptive cross-sectional study design was employed to collect data involving 350 participants, (doctors (29), nurses (96), and patients (225)) at KBTH's surgical department using the priori power calculation method. Participants were selected via purposive and convenience sampling. There was a pilot-tested electronic and paper questionnaire administered by trained research assistants. The instrument captured multidimensional perception indices (eg, clinical efficacy, convenience, economic burden) on validated Likert scales alongside socio-demographic and telehealth utilization covariates. Data were managed in REDCap with mandatory fields to minimize missing responses and anonymized identifiers to reduce bias. Analyses comprised descriptive statistics and proportions in IBM SPSS v26 and R v4.2.1. Results: A substantial 76.6% of stakeholders agree or strongly agree that telehealth reliably monitors minor postoperative conditions. Convenience and efficiency are paramount, with 82.9% of participants finding virtual follow-ups more convenient and 86.6% reporting significant time savings relative to in-person visits. Infection-control benefits are widely recognized (85.2%), and patient-provider rapport remains strong, with only 10.9% expressing discomfort. Major barriers include unstable broadband (83.4%), limited on-site technical support (66.0%), poor audiovisual quality (81.7%), and prohibitive data/device costs (61.4%). Key facilitators encompass robust security measures trusted by 73.8% of users, regulatory confidence (59.7%), perceived clinical equivalence (76.5%), and enhanced access for underserved populations (82.6%). Conclusion: Telehealth improves accessibility and efficiency in minor post-operative care. However, addressing technological barriers, insurance issues, and communication challenges is crucial. A hybrid approach integrating telehealth with in-person visits is recommended to enhance care quality and patient satisfaction.

Telemedicine in the pandemic of coronavirus disease 2019 (COVID-19) has responded to societal distancing in medical treatments by protecting health workers while also managing available resources. To attain best practices in telemedicine, a platform must be functional, and both patients and clinicians must be satisfied with the technology. To ensure the benefits of telehealth systems, usability refers to how easy the user interfaces of telehealth systems are to use. In this study, the usability of telemedicine systems has been investigated. Material and Methods: The authors of this study review the study from 2015 to 2021 using a combination of the keywords "health", "telemedicine", "telemedicine", "mobile health", "usability" "Software", "System" and "Program", which led to the extraction of 119 articles in this field. Results: Articles in the field of remote health software and evaluation of the usability of remote health applications in the form of applications based on mobile health technologies, web-based applications or a combination of both types with sample devices Primary are wearable electronics, sensors or robots. Conclusion: In this study, most of the remote health software are mobile based and their usability has been evaluated by a questionnaire. Satisfaction is the most important usability attributes to consider when designing Health mobile apps.

Artificial intelligence (AI) is reshaping healthcare delivery globally, yet its application in low-and middle-income countries (LMICs) remains limited. Nonprofit organizations are emerging as key actors in piloting affordable AI-based healthcare solutions for vulnerable communities. This paper examines the role of the Global Health Reform Initiative (GHRI), a nonprofit leveraging AI-driven digital platforms to improve healthcare access in Nigeria. By deploying chatbots, teleconsultations, and integrated referral systems, GHRI provides timely health information and connects underserved populations to appropriate medical care. The study highlights the potential of nonprofit-led AI interventions in overcoming systemic health challenges such as workforce shortages, rural-urban health disparities, and cost barriers. Findings suggest that AI, when embedded in nonprofit healthcare delivery, offers a scalable and inclusive model for strengthening health systems in LMICs.

Telehealth in the practice of pediatrics is fast changing the face of healthcare delivery in the global environment, but
in Nigeria the adoption is low owing to infrastructure, policy, and capacity shortages. This clinical initiative suggests
a strategic plan to develop pediatric telehealth in the Nigerian clinics, with an aim of closing the accessibility, quality
and continuity of care gaps of children, particular in underserved and rural populations. The initiative focuses on the
use of affordable, safe, and accessible to users telehealth platforms depending on the local context and is
complemented by the training of the healthcare providers to increase the level of digital competency, and remote
diagnostic features. It also promotes joint efforts of government agencies, stakeholders in the private sector, and
international health agencies in a bid to sustain funding, adhesion to regulations, and creation of awareness among the
people. This initiative has the potential to push the limit of timely pediatric consultations, alleviate avoidable morbidity
and enhance the overall outcomes of child health taking into consideration the existing penetration of mobile and
internet especially in the light of obstacles like lack of broadband and the accessibility and changes in cost of data and
data literacy. In the proposed approach, rather than a technological improvement, pediatric telehealth is viewed as an
essential and fair healthcare offering of the next generation of the Nigerian population.

The increasing proportion of elderly individuals worldwide has placed unprecedented demands on healthcare systems, particularly in the area of chronic wound management. Elderly patients are especially vulnerable to wounds such as pressure ulcers, diabetic foot ulcers, and venous leg ulcers, which require timely and continuous care to prevent complications and reduce mortality. However, traditional care models relying on frequent hospital or clinic visits are often unsuitable for older adults who face mobility constraints, transportation barriers, and heightened susceptibility to healthcare-associated infections. In this context, telehealth-enabled home-based wound care emerges as a transformative and sustainable solution that addresses both clinical and economic challenges. This article is a critical reflection on integration of telehealth technologies, home-based wound care service as a cost-effective solution, which fits the need of elderly population. Based on the systematic review of current clinical trials, economic research studies, and policy papers, the study proves that telehealth would shorten the duration of wound healing, enhance patient satisfaction, and cut down healthcare costs to a considerable degree because this intervention would reduce the number of hospitalizations and readmissions. Furthermore, the use of remote monitoring methods enables early recognition of the condition of wound deterioration and applying sufficient interventions in time, which leads to improved health outcomes.

Getting a medical travel cancellation certificate in Scotland has become increasingly convenient thanks to the rise of telehealth consultations and online doctor services. If you find yourself needing to cancel a trip due to a sudden illness or medical condition, having a valid medical certificate can be crucial for claiming refunds, rescheduling your travel plans, or handling insurance claims. This comprehensive guide will walk you through the step-bystep process of obtaining a medical travel cancellation certificate in Scotland, highlighting how doctor consultations and telehealth services streamline this often stressful situation. What is a Medical Travel Cancellation Certificate? A medical travel cancellation certificate is an official document issued by a qualified doctor that states you are unfit to travel for medical reasons. It typically includes your personal information, the nature of your illness or condition, the impact on your ability to travel, and a doctor's signature to verify authenticity. This certificate serves as a key piece of evidence when requesting refunds from travel companies, airlines, or making claims with travel insurance providers.

Background Artificial Intelligence (AI) is increasingly applied in healthcare to boost productivity, reduce administrative workloads, and improve patient outcomes. In nursing, AI offers both opportunities and challenges. This study explores nurses' perspectives on implementing AI in nursing practice within the context of Jordan, focusing on the perceived benefits and concerns related to its integration. Method A qualitative research approach was employed, involving semi-structured interviews with 25 nurses and 3 focus group discussions, each consisting of 7-8 participants. The data collected was coded and analyzed using thematic analysis to identify recurring patterns and key themes in the nurses' views on AI. Results Three major themes emerged from the analysis: (1) AI as an efficiency tool-Nurses recognized AI's ability to reduce administrative burdens and improve patient monitoring in real-time. (2) Ethical and practical concerns-Nurses raised issues regarding patient privacy, data security, and the fear that AI might replace human decisionmaking in care. (3) Lack of preparedness and training-There was a consensus on nurses' inadequate training in AI tools, limiting their ability to integrate AI into their practice fully. Conclusion While AI is seen as a valuable tool to enhance nursing productivity, several challenges still need to be addressed, particularly regarding ethical concerns and insufficient training. To ensure AI complements nursing without compromising the human element, healthcare institutions must address these issues by implementing comprehensive training programs and establishing clear ethical guidelines.

Access to healthcare services for individuals with disabilities is one of the key issues in modern health policies. Individuals with hearing and/or speech impairments encounter various communication barriers when accessing these services, resulting in inadequate delivery of care and communicationrelated challenges. However, effective communication is critical in healthcare for accurate diagnosis and the recovery process of patients. This research emphasizes that equal access to healthcare is a fundamental human right, and it demonstrates that the existing communication barriers also constitute a form of discrimination. In this context, artificial intelligence and digital health solutions are regarded not only as technological innovations but also as crucial tools for implementing inclusive health policies. The study particularly examines the potential of technologies such as telemedicine applications and automated sign language translation systems to enhance independent and equitable access to healthcare services for individuals with disabilities. These solutions improve accessibility by translating patient-doctor communication in real time into sign language and vice versa. It is argued that to effectively integrate these technologies into the healthcare system, accessibility standards must be legally mandated, and health policies should be restructured to address the specific needs of individuals with disabilities. Such a transformation would not only facilitate access to care for those with special requirements but also alleviate interpreter shortages in hospitals. The widespread adoption of digital health solutions and the adaptation of healthcare workers to these systems are critical steps toward making healthcare services more inclusive for individuals with hearing and/or speech impairments. This study offers recommendations for integrating digital health technologies into the healthcare system within the framework of inclusive health policies and disability rights, aiming to increase awareness and promote equitable healthcare for all.

The increasing proportion of elderly individuals worldwide has placed unprecedented demands on healthcare systems, particularly in the area of chronic wound management. Elderly patients are especially vulnerable to wounds such as pressure ulcers, diabetic foot ulcers, and venous leg ulcers, which require timely and continuous care to prevent complications and reduce mortality. However, traditional care models relying on frequent hospital or clinic visits are often unsuitable for older adults who face mobility constraints, transportation barriers, and heightened susceptibility to healthcare-associated infections. In this context, telehealth-enabled home-based wound care emerges as a transformative and sustainable solution that addresses both clinical and economic challenges. This article is a critical reflection on integration of telehealth technologies, home-based wound care service as a cost-effective solution, which fits the need of elderly population. Based on the systematic review of current clinical trials, economic research studies, and policy papers, the study proves that telehealth would shorten the duration of wound healing, enhance patient satisfaction, and cut down healthcare costs to a considerable degree because this intervention would reduce the number of hospitalizations and readmissions. Furthermore, the use of remote monitoring methods enables early recognition of the condition of wound deterioration and applying sufficient interventions in time, which leads to improved health outcomes.

Objective: To provide a glimpse of various digital programs and modules that are being implemented across the country by the National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India (an institution of national importance under the Ministry of Health and Family Welfare, Government of India; one of its mandates is to develop innovative strategies to improve mental health capacity building as part of the National Mental Health Program, a publicly funded health program to cater to the public health need posed by psychiatric disorders). Design: The information is presented in a narrative fashion by organizing the activities into three categories of digital training methods: webinar mode, blended mode and hybrid mode. Results: Cadres ranging from lay-counsellors (volunteers in the community), non-specialist health workers to professionals including medical officers are covered with these initiatives. During the period from August 2016 till December 2020, more than...

Background: Telemedicine is a fast-emerging health sector in India. While nurses play an important role in delivering healthcare services through telemedicine, little is known about whether nursing interns are prepared adequately. Aim: To evaluate nursing interns’ perceptions of telenursing and to find out their opinion on whether telenursing should be added to the curriculum. Methods: This was a cross-sectional descriptive survey carried out among conveniently selected nursing interns (N = 183) from renowned colleges in Bangalore, South India. The data were collected using a self-reported questionnaire. Results: In this study, a majority of the participants had smartphones (74.8%), were accessible to the internet (96.7%), and were using the internet for more than 3 h/day (73.3%). While a majority (65.6%) of the participants were able to correctly identify the definition of telenursing, only 33.9% of them rightly answered the definition of telemedicine. Most of the participants indi...

Older adults are at risk for low health literacy and not adhering to self-care. Health professionals are shifting their practices to emphasize wellbeing through health promotion. Mobile pain applications may be a tool to improve health communication and individualize care. Mobile health apps do not always consider the needs of the older adult who may be less comfortable and confident with technology. The purpose of this qualitative review is to explore mobile pain applications for adults with a health literacy framework, and identify facilitators and barriers to usability. Databases that reviewed apps included Google, Google Scholar, ScienceDirect, PubMed, CINAHL plus full text, APTA EBP database, MEDline, and SportDiscus. Fifty-three apps found. Excluded criteria: if there was a cost, targeted for children, and without pain diary. Six apps identified to be specifically relevant to pain intensity, location quality, and impact on life. Mobile Application Rating System (MARS) tool ass...

were conducted in a convenience sample of women age 65+, post-primary treatment for Stage I-III breast cancer, who received in-person outpatient care at NC Cancer Hospital before transitioning to telemedicine after March 2020. Patients were interviewed about their perceptions of telemedicine (telephone, video) as compared to in-person visits. Audio files of interviews were transcribed and reviewed to identify themes established a priori in the interview protocol. 15 patients (telephone=5, video=10) were consented and interviewed (July-October 2021), mean age=74. 13/15 participants reported that they preferred a hybrid care model that included telemedicine care over in-person care alone. COVID-19, physical disability, and transportation burden were associated with telemedicine preference. Comfort with familiar patient-provider interaction and lack of physical exam were associated with in-person appointment preference. Patient-clinician conversations and clinic protocols guiding use of telemedicine should take into account newness of diagnosis, patient comfort and familiarity with the care team, travel burden, disability, and whether the physical exam is or is not essential.

Background The development of e-health technologies for teleconsultation and exchange of knowledge is one of the core purposes of European Reference Networks (ERNs), including the ERN EURO-NMD for rare neuromuscular diseases. Within ERNs, the Clinical Patient Management System (CPMS) is a web-based platform that seeks to boost active collaboration within and across the network, implementing data sharing. Through CPMS, it is possible to both discuss patient cases and to make patients’ data available for registries and databases in a secure way. In this view, CPMS may be considered a sort of a temporary storage for patients’ data and an effective tool for data sharing; it facilitates specialists’ consultation since rare diseases (RDs) require multidisciplinary skills, specific, and outstanding clinical experience. Following European Union (EU) recommendation, and to promote the use of CPMS platform among EURO-NMD members, a twelve-month pilot project was set up to train the 15 Italian...

Background The future of digital health holds enormous potential to improve communication with patients and optimize the delivery of care. The current study aims to answer the central question of which knowledge, skills, and competencies in the use of Information and Communication Technologies (ICT), health professionals should develop to promote efficient remote communication processes with patients. Methods A mixed-method approach was used for data collection, combining an online survey with semi-structured interviews. The study was structured into four key phases/question groups: professional context, practices related to the use of ICT in patient communication, training needs, and other relevant information. Qualitative data from open-ended responses were analysed using thematic analysis and triangulated with quantitative findings where applicable. The target population consisted of nursing professionals with patient care experience. The survey was distributed electronically, with 194 nurses fully or partially completing the questionnaire. Additionally, 24 interviews were conducted. Results The data shows that around 25.85% of professionals do not establish distance communication and 95.4% do not use telehealth. Telephone and cellular contact are the most used means of communication with patients (62.60%). Despite the predominance of face-to-face care, 62.5% stated that they do not experience difficulties or concerns, recognizing ICT as an increasingly integrated and advantageous tool for remote communication. Most professionals (80.1%) believe that there should be more training and courses in digital communication with patients and the use of ICT in healthcare, to address gaps in academic training. The growth of telemedicine and the digitalization of healthcare services reinforce the need for continuous professional training in this area. Conclusions Most professionals have a positive perception of the opportunities created by emerging technologies, but they also express concerns about the ethical, social, safety and technical challenges that need to be addressed. The introduction of mandatory ICT courses in academic education and the implementation of continuous training are essential to prepare professionals for the challenges of telehealth and digital communication in healthcare. They emphasize the need for a well-structured digital transition, ensuring that technologies complement healthcare rather than replace human care.

This study explores the use of big data analytics for real-time patient monitoring and risk prediction. By processing vast, diverse health data streams, the system enables continuous tracking of patient conditions and early identification of potential risks, thereby supporting timely interventions and improving overall clinical outcomes and patient safety.

Some intentionally popular sources are as follows. All are good, with McNeill ' s as the most formal and scholarly, but still easy reading. Bryson is a popular humorist and witty observer of British and US cultural differences. From 1990 to 1997 Gonick penned a bimonthly " Science Classics " cartoon for Discover Magazine. Science fi ction writers and science popularizers have often undertaken similar tasks to give themselves " the big picture " and share it with the public. It is also worthwhile to hunt out Isaac Asimov ' s Chronology of the World , and H. G. Well ' s much earlier classic A Short History of the World .

This report provides a comprehensive literature overview of Digital Health and Artificial Intelligence (AI) in healthcare within Bulgaria, aligning with the "Digital Health: Implementation, Governance, Deliberation" project (BG-RRP-2.2018-0004). The Bulgarian government views digital transformation in healthcare as a key national priority, aiming to improve quality of life and service delivery, notably through the National Health Strategy 2030.

The methodology involved a profound literature review using both manual and AI-assisted searches across academic repositories and national/European reports. The objective is to map the evolution of digital health implementation in Bulgaria, identify strengths and weaknesses, and propose a Framework for Implementation, Governance, and Democratic Deliberation of digital health (FIGDD). This will inform future empirical research, including questionnaires and interviews with medical personnel, to ensure alignment with national, European, and WHO standards.

While Bulgaria has made significant strides, particularly with the post-2020 acceleration in digitalization and the successful implementation of the National Health Information System (NHIS), challenges persist. These include a fragmented legal framework, issues with data interoperability, and existing digital literacy gaps among professionals and patients. Although an AI strategy is in place, Bulgaria's scientific output in this field remains modest. The report highlights governmental strategies, university involvement, emerging HealthTech startups, and discussions on ethical and philosophical considerations surrounding AI in medicine. The findings underscore the need for continued investment, regulatory clarity, and enhanced digital education to foster a truly integrated and patient-centered digital healthcare ecosystem in Bulgaria.

The advancement of digital health systems has increased the need for interoperability across heterogeneous platforms in modern healthcare institutions. Health Level Seven (HL7) and Digital Imaging and Communications in Medicine (DICOM) have emerged as two of the most widely adopted industrial standards supporting textual and image-based data exchange, respectively. This paper provides a conceptual introduction to both standards, elaborating on their structure, function, and role in hospital information systems (HIS), radiology information systems (RIS), and picture archiving and communication systems (PACS). HL7, with its structured messaging format, facilitates the exchange of administrative and clinical data across systems, while DICOM ensures standardized communication of medical imaging. The fragmentation of healthcare data, often due to vendor-based system differences, presents challenges that can be addressed through the implementation of HL7-DICOM gateways. These gateways enable seamless integration of textual and image data between systems, thus enhancing the continuity and safety of patient care. This paper also discusses the architecture and function of such a gateway, as well as the significance of using international standards to support interoperability and data consistency in healthcare environments.

Background and Aims: Better understanding the challenges faced by patients on medications for opioid use disorder (MOUD), including methadone and buprenorphine, is critical to increasing their use/retention. Social media platforms such as Reddit offer a space for patients to share their experiences with medications. We aimed to identify and characterize challenges faced by patients taking MOUD through analysis of discussions from the r/Methadone and r/suboxone subreddits.

Increasingly, cloud computing is transforming how data is managed and analyzed financially, providing scalable and secure solutions for SMEs and healthcare applications. Nevertheless, the remote patient monitoring (RPM) systems that have been established thus far encounter problems such as high latency, a poor usage of available bandwidth, as well as vulnerabilities in data security, thus restricting healthcare decision-making in real-time. Traditional encryption and authentication methods do not hold enough value against new-age evolving cyber threats and thus risk patient data privacy, whereas established means of data transmission do not prioritize significant health parameters leading to bring about delayed emergency response. E-RPM revolves proposing a very cost effective and safe Remote Patient Monitoring system on an integrated multi-parameter wearable device, cloud computing, and priority-based optimization of data transmission process for real-time health monitoring. Threats are detected using AI on hybrid encrypted data and then authenticated through multiple factors so that the system provides integrity of data as well as patient privacy and secured communication. The crux of this includes noise reduction and normalization of health data preprocessing, compression of data for high efficiency in storage and transmission, then the last nugget would be Convolutional Neural Networks (CNN) for predictive health analytics. It decreases congestion and proposes a priority-based transmission model which utilize bandwidth for real-time delivery of critical health data and reduced latencies.

The goal of this study is to improve patient care and enable real-time decision-making by enhancing an advanced Internet of Things (IoT)-based healthcare system using fog computing, data routing algorithms, and Artificial Intelligence (AI) models. AI models for anomaly detection, fog computing for low-latency data processing, IoT devices for continuous patient data collecting, and improved data routing for smooth communication between cloud systems, fog nodes, and IoT devices are all integrated into the system. Incorporating mathematical models for data routing optimization, latency minimization, and AI training ensures system scalability, accuracy, and efficiency. By reducing latency, increasing throughput, and improving decision-making accuracy, the suggested solution successfully tackles issues in real-time healthcare monitoring. Healthcare service delivery has significantly improved when performance is evaluated using important parameters such as accuracy, dependability, scalability, throughput, energy usage, and latency. The system achieves an overall accuracy of 96.8%, according to the data, which is a significant improvement above traditional methods. In addition to improving the effectiveness of real-time patient monitoring, this integrated strategy opens the door for context-aware, adaptive, and predictive healthcare solutions, which will ultimately improve patient outcomes and healthcare infrastructure.

The rapid growth of eHealth technologies has transformed global healthcare delivery, enhancing patient care, access, and efficiency, particularly in underserved regions. This review synthesizes studies on AI-driven diagnostics and telemedicine, highlighting their potential impact on healthcare systems. Despite these advancements, challenges such as data privacy, ethical issues, and infrastructural barriers remain, along with global disparities in eHealth adoption. The review adopts a systematic approach, analyzing studies from regions like Tanzania, Poland, Spain, and Malaysia, offering a global perspective on digital health innovations. The systematic review analyzed AI-driven eHealth technologies by applying rigorous eligibility criteria, focusing on study design, geographical diversity, technological innovations, and measurable outcomes. It selected peer-reviewed articles from 2024, emphasizing studies on diagnostics, IoT integrations, and mental health. The selection process included studies from both developed and developing regions, ensuring global perspectives. Data extraction and thematic analysis identified key themes such as AI applications, global insights, challenges, opportunities, and ethical considerations, providing a comprehensive synthesis of AI's transformative impact on healthcare delivery. Notably, it examines the integration of AI, IoT, and the intersection of eHealth with environmental sustainability. Findings show that AI improves diagnostic accuracy and patient outcomes, while IoT and edge computing enhance real-time data processing, especially in remote monitoring and telemedicine. Teleconsultations further contribute to sustainability by reducing travel. However, data privacy and ethical concerns highlight the need for strong regulatory frameworks. The review concludes that eHealth technologies hold transformative potential, but secure, ethical, and equitable implementation is crucial. Implications include enhanced healthcare access, efficiency, and environmental benefits. Limitations involve infrastructural disparities and data governance issues. Future research should focus on scalable, secure eHealth models and address ethical challenges surrounding AI to ensure sustainable, equitable healthcare development.

Latar belakang: Akses layanan kesehatan di Indonesia masih belum merata, terutama di wilayah 3T (tertinggal, terdepan, dan terluar), yang mengalami kekurangan tenaga medis dan fasilitas kesehatan. Telemedicine sebagai layanan kesehatan berbasis teknologi digital muncul sebagai solusi potensial untuk mengatasi hambatan geografis dan meningkatkan akses layanan medis di daerah terpencil. Metode: Penelitian ini menggunakan metode tinjauan pustaka (literature review) yang dilakukan secara sistematis, eksplisit, dan dapat direproduksi untuk mengidentifikasi, mengevaluasi, serta mensintesis karya-karya ilmiah dan pemikiran yang telah dihasilkan oleh para peneliti maupun praktisi. Hasil dan Pembahasan: Hasil kajian menunjukkan bahwa telemedicine memiliki peluang besar dalam meningkatkan akses, efisiensi biaya, dan kapasitas layanan di wilayah terpencil. Telemedicine mempermudah konsultasi medis, pemantauan penyakit kronis, dan pelatihan tenaga kesehatan. Namun, tantangan utama dalam implementasi meliputi keterbatasan infrastruktur TIK, rendahnya literasi digital, kurangnya perlindungan data pasien, serta regulasi hukum yang belum komprehensif. Kesimpulan: Telemedicine memiliki potensi besar dalam pemerataan layanan kesehatan di Indonesia, tetapi perlu didukung oleh kebijakan yang jelas, pembangunan infrastruktur digital, peningkatan literasi digital, serta jaminan keamanan data pasien. Implementasi telemedicine yang berkelanjutan memerlukan kolaborasi antara pemerintah, tenaga kesehatan, penyedia layanan teknologi, dan masyarakat.

Digital health is the convergence of digital technology in healthcare. The emerging technology and the use of changes are needed in healthcare for advancements and better outcomes. With the use of new innovations, new threats and challenges are emerging in the industry, which needs to be managed for efficient operations. The paper talks about the rising demand for integrating data with highly enabled technologies in the field of medical, biomedical, and healthcare. The availability of data at the central location of any Medical or healthcare organization would primarily serve the major concern of data availability with security. At the same time, the data is being treated in terms of data security and healthcare privacy as the key to improving issues related to the same and also to gain insights and lower the costs. This paper aims to present the digital healthcare and privacy that applies to the healthcare industry and also to discuss the advancements that are being implemented in ...

Due to the emergence of social networking sites and social media platforms, there is faster information dissemination to the public. Unverified information is widely disseminated across social media platforms without any apprehension about the accuracy of the information. The propagation of false news has imposed significant challenges on governments and society and has several adverse effects on many aspects of human life. Fake News is inaccurate information deliberately created and spread to the public. Accurate detection of fake news from cyber propagation is thus a significant and challenging issue that can be addressed through deep learning techniques. It is impossible to manually annotate large volumes of social media-generated data. In this research, a hybrid approach is proposed to detect fake news, novel weakly supervised learning is applied to provide labels to the unlabeled data, and detection of fake news is performed using Bi-GRU and Bi-LSTM deep learning techniques. Feature extraction was performed by utilizing TF-IDF and Count Vectorizers techniques. Bi-LSTM and Bi-GRU deep learning techniques with Weakly supervised SVM techniques provided an accuracy of 90% in detecting fake news. This approach of labeling large amounts of unlabeled data with weakly supervised learning and deep learning techniques for the detection of fake and real news is highly effective and efficient when there exist no labels to the data.

As an extension to the service delivery framework of the existing National Mental Health Programme, the Tele-Mental Health Assistance and Networking Across States (Tele-MANAS) initiativewas announced in the Union Budget in February 2022. It aims to provide universal access to equitable, accessible, affordable, and quality mental healthcare
through 24X7 tele-mental health counselling services as a digital component of the National Mental Health Programme (NMHP and its operational arm, the District Mental Health Program/DMHP) across all Indian States and UTs with assured linkages. This guide introduces the toolkit to be used by the facilitators in training the Tele MANAS
Counsellors. It will help to shed light on the methodology, focus, and techniques in teaching the modules to the trainers. We recommend reading this manual before training the Tele-MANAS Counsellors. A brief overview of the topics covered in each of the modules - Modules 1 to 22 - includes a brief description of what is to be taught.

Mobile technology is emerging as the first extensive form of electronic communication which is culturally and socially feasible and appropriate for strengthening health system. As a public health intervention, the world of mobile is just beginning. The essay analyses the role of mobile technology for public health by using 4 Ps of marketing mix-products and services, price, place, and promotion from social marketing perspective and also show how it helps for democratizing public health programs in the developing world.

Introduction: Stroke is a leading global contributor to mortality and disability. Low-and middle-income countries are disproportionately affected and account for 87% of stroke-related disabilities and 70% of stroke-related fatalities. The challenges of stroke care accessibility in Africa are compounded by financial constraints, geographical barriers, and inadequate healthcare infrastructure, necessitating the adoption of innovative models such as telestroke. Telestroke is a critical component of modern stroke care systems. Telestroke enables real-time remote assessments, optimizes patient triage and hospital transfers, improves the efficiency of thrombolysis administration, and enhances poststroke management by mitigating logistical and mobility-related challenges. This demonstrates telestroke's potential to expand access to specialized stroke care, improve functional outcomes, and address critical gaps in stroke management within underserved regions such as Africa. This paper assesses the advantageous impact of telestroke on stroke management, with the aim of drawing global insights for Africa. Methodology: This scoping review adhered to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines. A comprehensive search was conducted across ProQuest, PubMed, Google Scholar, and Scopus to identify peer-reviewed studies published in English from 2017 to 2023. This ensured the inclusion of the most recent advancements in telestroke research. Results: The initial literature search retrieved 881 articles, of which 143 duplicates (16.2%) and 58 non-English studies (6.6%) were removed, followed by the exclusion of 451 nonpeer-reviewed publications (51.2%) and 128 articles (14.5%) unrelated to the study area, leaving 101 studies (11.5%) for full-text review. After further screening, 70 studies were excluded for not aligning with the study's title, objectives, or key search terms. This resulted in 31 studies (3.5%) being included in the final analysis, with 21 studies originating from outside Africa. The limited availability of high-indexed, peer-reviewed African telestroke studies highlighted a research gap, impacting the generalizability of findings. Conclusion: Telestroke has demonstrated significant benefits in stroke management, including improved functional outcomes, reduced onset-to-treatment time, enhanced diagnostic accuracy, and increased healthcare accessibility, particularly in medically underserved regions. However, its implementation in Africa faces challenges related to ethical concerns, technological infrastructure, regulatory inconsistencies, financial sustainability, and limited clinician buy-in. This necessitates strategic interventions such as standardized regulatory frameworks, network expansion, sustainable financing, capacity-building, and the integration of cost-effective imaging technologies to enhance stroke care delivery across the continent.

This overwhelming demand puts a lot of pressure on already strained healthcare services and contrives to bring out the inefficiencies that travel deep within them, calling for new solutions. At the same time, strict lockdowns, with mandatory social distancing significantly decreased the opportunities of more conventional, face-to face medical consultations thus many patients remained unserved or underserved. To these challenges, telemedicine emerged quickly as a preferable option to practice healthcare away from the traditional centralized healthcare facilities. Telemedicine lets the patients talk to the doctors, get a diagnosis, or even get prescribed medication all from the safety of their own home. Moreover, incorporation of artificial intelligence (AI) in telemedicine greatly enhanced this solution to an enhanced level of technological advancement.

The emergence of medical informatics as a new ICT application is due to the rapid advances in computing and communications technologies, an increasing awareness that the knowledge base of biomedicine is essentially unmanageable by traditional paper-based methods, and a growing conviction that the process of informed decision making is as important to modern biomedicine as is the collection of facts on which clinical decisions are taken. Health informatics is a wide-ranging science incorporating the complex mixture of people, organizations, illnesses, patient care and treatment. It is a scientific application that deals with the storage, retrieval, sharing, and optimal use of biomedical information, data, and knowledge for problem solving and decision making. The application touches on all basic and applied area in biomedical science and is closely tied to modern information technologies, notably in the areas of computing and communication. Health informatics looks into ways to optimize clinical knowledge creation, sharing and application to deliver better healthcare and to promote health.

Background: Store-and-forward telehealth (SFT) is the asynchronous sharing of photo images or short video clips from patients to providers, with patients using their own digital devices. Objective: We aimed to enhance patient assessment and increase the use of SFT among providers within a remote patient monitoring-home telehealth (RPM-HT) program. Methods: The design for this pilot project was descriptive. It was a 3-month pilot project conducted within a local RPM-HT program that provides nursing care to patients with chronic health conditions in a large regional healthcare facility in the Southeastern United States. We conducted the pilot using the Plan-Do-Study-Act process improvement framework. Twenty registered nurse (RN) care coordinators were asked to identify two clinical opportunities for using SFT. Patients uploaded the images or videos via the virtual care management system. The goal was for the patient to upload 40 to 50 high-quality clinically significant video clips or images and use the image for a clinical encounter. An RN care coordinator survey solicited insight about the provider experience. Results: Of the 81 patients who agreed to submit an image or a video, 30% submitted at least one image or video, for a total of 42 useable images. The RN care coordinators were generally positive about the use of SFT in RPM-HT, citing better opportunities for physical assessment and improved patient access to care. Discussion: Integrating the use of SFT into RPM-HT provides opportunities for improved care coordination and enhanced clinical assessment, plus a new opportunity for patient access. Wider implementation of SFT into similar programs may improve patient outcomes. The outcome was the creation of a user-friendly process for integrating SFT into the RPM-HT program. Challenges included patient and provider participation and patient use of technology.

Background: With the increasing acceptance of face-to-face classes transitioning to web-based learning due to COVID-19, there is an increasing need to have educators trained and equipped to teach online. The ability to teach in-person may not necessarily mean that one is ready teach in a web-based environment. Objective: The objective of our study was to investigate the readiness of health care professionals in Singapore to teach online and their technology-related teaching needs. Methods: This was a quantitative cross-sectional pilot study conducted among health care administrative staff and professionals in medicine, nursing, allied health, and dentistry. Participants were recruited via an open invitation email to all staff members of Singapore's largest group of health care institutions. Data were collected using a web-based questionnaire. Differences in the readiness of the professionals to teach online were analyzed using analysis of variance, and a 1-sided independent sample t test was performed to analyze the differences between respondents younger than 40 years and those older than 41 years. Results: A total of 169 responses was analyzed. Full-time academic faculty members scored the highest for readiness to teach online (2.97), followed by nursing professionals (2.91), medicine professionals (2.88), administrative staff members (2.83), and allied health professionals (2.76). However, there was no statistically significant difference (P=.77) among all the respondents in their readiness to teach online. There was an agreement among all professionals in their need for software tools to teach; in particular, there was a significant difference in the software needs among the professionals for streaming videos (P=.01). There was no statistically significant difference in the readiness to teach online between those younger than 40 years and those older than 41 years (P=.48). Conclusions: Our study shows that there are still some gaps in terms of readiness to teach online among health care professionals. Our findings can be used by policy makers and faculty developers to identify opportunities for development among their educators so that they are ready to teach online with the appropriate software tools.

The goal of this study is to improve patient care and enable real-time decision-making by enhancing an advanced Internet of Things (IoT)-based healthcare system using fog computing, data routing algorithms, and Artificial Intelligence (AI) models. AI models for anomaly detection, fog computing for low-latency data processing, IoT devices for continuous patient data collecting, and improved data routing for smooth communication between cloud systems, fog nodes, and IoT devices are all integrated into the system. Incorporating mathematical models for data routing optimization, latency minimization, and AI training ensures system scalability, accuracy, and efficiency. By reducing latency, increasing throughput, and improving decision-making accuracy, the suggested solution successfully tackles issues in real-time healthcare monitoring. Healthcare service delivery has significantly improved when performance is evaluated using important parameters such as accuracy, dependability, scalability, throughput, energy usage, and latency. The system achieves an overall accuracy of 96.8%, according to the data, which is a significant improvement above traditional methods. In addition to improving the effectiveness of real-time patient monitoring, this integrated strategy opens the door for context-aware, adaptive, and predictive healthcare solutions, which will ultimately improve patient outcomes and healthcare infrastructure.

This study focuses on ECG monitoring and investigates how cloud computing, fog computing, and IoT can be used to create scalable and efficient healthcare solutions. Patients' ECG signals are continuously collected by IoT devices and analyzed locally at fog nodes, which ensures minimal latency and lessens the strain on the cloud. By processing data near the source, fog computing allows for quicker reaction times and instantaneous analysis and decision-making. Cloud computing enhances fog by offering large-scale storage, processing capacity, and robust machine learning models for analyzing huge datasets-all of which are essential for long-term storage and precise forecasting. ECG signals are used to identify abnormal heart conditions like arrhythmias or ischemia using machine learning-driven approaches like feature extraction and anomaly identification. This improves the precision of diagnosis and makes prompt actions possible. When compared to conventional systems, the system's 94% accuracy in real-time ECG analysis greatly increases anomaly detection rates and scalability. In addition to improving the system's scalability and efficiency, the combination of cloud, fog, and IoT also makes it possible for the system to manage large data streams with little latency. Cloud and fog computing together create new opportunities for healthcare systems to become more precise, responsive, and efficient, setting the stage for the future of digital healthcare.

Introduction: Recent advancements in information technology and access to smartphone have expanded the scope of healthcare delivery services across the globe. Telemedicine is making healthcare affordable and more accessible to the needy in situations like the present pandemic. Although telepsychiatry services were underutilised initially in India due to various barriers, its role in delivering healthcare services, has gained pace since the last few years. During the coronavirus disease (COVID-19) pandemic, India introduced telemedicine practice guidelines (March, 2020), and telepsychiatry operational guidelines (May, 2020), to remove barriers and promote equitable access. In the wake of COVID-19 pandemic various mental health institutes across India relied heavily upon telepsychiatry services to provide care. National Institute of Mental Health and Neuro Sciences, Bangalore being an Institute of National Importance has introduced different modules to provide clinical care to the men...

The study examines the intricate relationship between perceived social support and psychological well-being, with a particular focus on the moderating effects of self-esteem, social interactions, and social comparison. While digital media has revolutionized social connectivity, gaps remain in understanding its dual role in fostering mental health and exacerbating psychological distress. The study employs a quantitative research methodology with a survey-based approach targeting Malaysian social media users to investigate these dynamics. Structural equation modeling (SEM) and reliability measures reveal significant mediating effects of perceived social support on mental health, emphasizing its potential to buffer stress and enhance psychological resilience. Findings highlight how supportive digital interactions can mitigate the adverse impacts of upward social comparisons while promoting self-esteem and overall well-being. The study contributes novel insights into how perceived social support interacts with digital engagement to shape mental health outcomes, integrating both traditional and virtual support systems. Results indicate that perceived social support substantially improves psychological well-being and moderates the adverse effects of social comparison on self-esteem. Additionally, while social media platforms provide avenues for emotional support and social validation, overreliance on virtual interactions can exacerbate dependency and reduce real-world connections. The study underscores the necessity for balanced engagement strategies to maximize the positive aspects of digital interactions while minimizing risks. Limitations include the geographically constrained sample and a reliance on self-reported data, which may introduce bias. Future research should explore longitudinal and experimental designs to establish causal relationships and extend findings to diverse populations. The implications of this study are far-reaching, offering valuable guidance for mental health interventions and digital platform design, fostering a supportive online environment for improved mental well-being.

The study explores the complex relationship between self-esteem, social support, and digital health engagement. It examines how self-esteem influences emotional, cognitive, and social well-being, and the role of social support in enhancing self-esteem. Additionally, it investigates how digital health platforms impact self-esteem and mental health outcomes. The study addresses gaps in existing research, particularly in non-Western cultural contexts, and emphasizes the role of resilience in moderating the effects of digital health on mental well-being. This research employs a quantitative approach within a positive framework to investigate the relationship between digital health engagement, selfesteem, perceived social support, and psychological well-being among 400 users. A questionnaire survey was administered using Google Forms to collect data from a purposive sample of digital health users. The study analyzes these data to test hypotheses regarding the influence of selfesteem and perceived social support on psychological well-being, with digital health engagement as a potential mediator. The study found significant positive relationships between self-esteem, perceived social support, and perceived well-being. Perceived social support was identified as a strong predictor of perceived well-being (β = 0.605, p = 0.000), while self-esteem positively influenced both perceived social support (β = 0.103, p = 0.007) and perceived well-being (β = 0.071, p = 0.022). The collinearity assessment showed no issues, with all variance inflation factors (VIFs) below the threshold of 3, indicating that multicollinearity was not a concern in the model. Furthermore, the mediation analysis revealed that perceived social support partially mediates the relationship between self-esteem and perceived well-being (VAF = 46.62%, p = 0.008), suggesting that while social support plays a significant role, other factors likely contribute to the relationship. All hypotheses in the study were supported, emphasizing the importance of fostering self-esteem and social support to improve mental health and well-being. These findings highlight the potential of digital health interventions in enhancing psychological factors to promote overall well-being. Self-esteem significantly enhances psychological well-being, influencing mental health positively. Recommendations for improving mental health include implementing intervention programs in schools and workplaces, using cognitive-behavioral techniques, and promoting digital health literacy.

Background: Physician autonomy has been found to play a role in physician acceptance and adoption of artificial intelligence (AI) in medicine. However, there is still no consensus in the literature on how to define and assess physician autonomy. Furthermore, there is a lack of research focusing specifically on the potential effects of AI on physician autonomy. Objective: This scoping review addresses the following research questions: (1) How do qualitative studies conceptualize and assess physician autonomy? (2) Which aspects of physician autonomy are addressed by these studies? (3) What are the potential benefits and harms of AI for physician autonomy identified by these studies? Methods: We performed a scoping review of qualitative studies on AI and physician autonomy published before November 6, 2023, by searching MEDLINE and Web of Science. To answer research question 1, we determined whether the included studies explicitly include physician autonomy as a research focus and whether their interview, survey, and focus group questions explicitly name or implicitly include aspects of physician autonomy. To answer research question 2, we extracted the qualitative results of the studies, categorizing them into the 7 components of physician autonomy introduced by Schulz and Harrison. We then inductively formed subcomponents based on the results of the included studies in each component. To answer research question 3, we summarized the potentially harmful and beneficial effects of AI on physician autonomy in each of the inductively formed subcomponents. Results: The search yielded 369 studies after duplicates were removed. Of these, 27 studies remained after titles and abstracts were screened. After full texts were screened, we included a total of 7 qualitative studies. Most studies did not explicitly name physician autonomy as a research focus or explicitly address physician autonomy in their interview, survey, and focus group questions. No studies addressed a complete set of components of physician autonomy; while 3 components were addressed by all included studies, 2 components were addressed by none. We identified a total of 11 subcomponents for the 5 components of physician autonomy that were addressed by at least 1 study. For most of these subcomponents, studies reported both potential harms and potential benefits of AI for physician autonomy. Conclusions: Little research to date has explicitly addressed the potential effects of AI on physician autonomy and existing results on these potential effects are mixed. Further qualitative and quantitative research is needed that focuses explicitly on physician autonomy and addresses all relevant components of physician autonomy.

SummaryObjectives: Assess unforeseen consequences of Telehealth and suggest solutionsMethods: An outline was created collecting all possible ill effects classified into Clinical considerations, Administrative concerns including interpersonal relations, Technical issues, Legal / Ethical concerns and Miscellaneous. Each topic was assigned to a particular WG member to lead, gather opinion and review existing literature.Results and Conclusion: A wide array of problems have been described. Except for technical issues, literature on this topic is scant, so this article is based more on personal experience and data collected from surveys. Much can be done to prevent such problems, such as a need for standardization with related clinical studies for devices as well as processes used for telehealth is underlined, besides evaluation of outcomes of projects undertaken.