The main aim of this article is to reflect on the impact of biases related to artificial intelligence (AI) systems developed to tackle issues arising from the COVID-19 pandemic, with special focus on those developed for triage and risk... more
Independents agents have long been a analysis centre in academic and industry production group. Early analysis frequently focuses on instruction agents with little knowledge within isolated environments, which diverges notably from being... more
This paper explores the development and evaluation of physics-specific large-scale AI models, which we refer to as large physics models (LPMs). These models, based on foundation models such as large language models (LLMs) are tailored to... more
Modeling the dependencies among multiple temporal attributes derived from integrated healthcare databases represents an unprecedented opportunity to support medical and administrative decisions. However, existing predictive models are not... more
Blockchain technology has gained increasing attention in recent years due to its capacity to provide secure, decentralized, and tamper-evident data storage. Within healthcare, these attributes offer the potential for streamlined data... more
Early Detection: AI analyzes vast data; detecting subtle disease cues (cancer, TB) for earlier, proactive interventions and improved outcomes. Beyond Individuals: AI scans populations, predicting outbreaks and risk factors, guiding... more
Η ψηφιακή τεχνολογία έχει μετασχηματίσει ριζικά τον τομέα της υγείας, από τους ηλεκτρονικούς φακέλους και την τηλεϊατρική έως τη χρήση τεχνητής νοημοσύνης στη διάγνωση και τη θεραπεία. Παρά τα σημαντικά οφέλη, οι καινοτομίες αυτές... more
Artificial Intelligence (AI) is increasingly the innovative driver in neonatal care, powering breakthroughs in early diagnosis, predictive analytics, surgical planning, and intense monitoring of care. AI technologies are increasingly... more
Telemedicine is an important solution for increasing the availability of health care services, with an emphasis on adequate geographic distribution, which enhances the fairness of health care service delivery. The research also outlines... more
Healthcare organizations worldwide face a fundamental challenge: they need large, diverse datasets to develop effective treatment protocols and diagnostic tools, yet privacy laws and institutional policies prevent traditional data... more
As large language models (LLMs) increasingly mediate cross-cultural communication, their behavior still reflects the distributional bias of the languages and viewpoints that are over-represented in their pre-training corpora. Yet, it... more
National Accreditation Board for Hospitals and Healthcare Providers (NABH) over the years has established itself as a beacon for creating an ecosystem of quality healthcare in India and has played a crucial role in driving the healthcare... more
The article explores the transformative role of Artificial Intelligence (AI) in the legal profession, highlighting its diverse applications and the ethical challenges it raises. AI's potential to reshape legal systems is examined through... more
Background: Transfusion-dependent beta-thalassemia presents a significant public health challenge in Pakistan, with an estimated 5,000 to 9,000 children born with the condition annually. These patients require lifelong management,... more
Artificial intelligence (AI) is the simulation of human intelligence in computers. It is designed to think and behave like human beings. The basic aim of creating AI machines is to make computer systems that can learn, adapt, and... more
Artificial intelligence (AI) is the simulation of human intelligence in computers. It is designed to think and behave like human beings. The basic aim of creating AI machines is to make computer systems that can learn, adapt, and... more
As quantum computing and AI converge in cybersecurity, strong ethical and regulatory frameworks are essential. This chapter examines challenges posed by quantum AI in threat detection, including concerns over data sovereignty, bias,... more
The intersection of health, climate, and artificial intelligence represents both a challenge and an opportunity. This book explores how Cognitive AI — combining deep learning, reasoning, and interpretability — can address pressing issues... more
Background: Artificial intelligence (AI) shows strong potential to transform primary care by streamlining workflows, improving diagnostics, and enhancing patient outcomes. However, integration faces barriers, including PCPs' concerns... more
The current global issue of the COVID-19 pandemic has prompted the push and utilization of all available means to halt its spread. COVID-19 is a highly infectious disease, and continuously monitoring early symptoms could help avert... more
Dengue remains a significant problem that needs to be addressed urgently in Thailand. Although Thailand has spread the dengue fever for more than sixty years, however, it is still found dengue patients in every province and spread to... more
Healthcare is being transformed by AI-driven visualization, which transforms complex data into useful insights. This paper synthesizes advancements in AI visualization tools-spanning medical imaging, electronic health records (EHR),... more
The increasing global burden of chronic diseases, which accounts for nearly 70% of healthcare costs, has driven a paradigm shift toward preventive healthcare strategies emphasizing early detection and intervention. Predictive... more
The use of Information and Communications Technology (ICT) in health systems is increasing worldwide. While it is assumed that ICT holds great potential to make health services more efficient and grant patients more empowerment, research... more
This exploratory study investigates the potential trajectories of education through a unique thought experiment conducted using three artificial intelligence (AI)-powered chatbots, namely GPT-4o, Gemini 2.0 Flash, and DeepSeek R1. The... more
Artificial intelligence (AI) is fundamentally reshaping diagnostic medicine, signaling a paradigm shift from episodic and reactive care to continuous, predictive, and precision-guided healthcare. In particular, AI-driven imaging systems... more
Macular edema (ME) is among the most prevalent retinal conditions, resulting from the accumulation of fluid that causes the retinal layers at the macula to separate. This study explores a computer-aided approach for detecting even subtle... more
The integration of digital health systems has transformed healthcare delivery worldwide. Among these, Electronic Medical Records (EMRs) and Electronic Health Records (EHRs) are often used interchangeably, yet they differ in scope,... more
► This will be the first trial to evaluate the effectiveness of protocolled practice nurse-led care for children with asthma in primary care. ► Asthma in children is a clinical diagnosis for which no 'gold standard' diagnostic criteria... more
The need to record information regarding a patient has been considered as an old, but important issue within the medical arena. Recently, much progress has been noted in the process of collection, storage, and retrieval of patients‘ data,... more
aims to provide a comparative analysis to help healthcare providers make data-driven decisions when selecting an optimal management system. With the increasing adoption of digital solutions in healthcare, selecting a robust and scalable... more
Reconstructing Reason in AI: An ESSIM Model to Address Structural Failures in Large Language Systems
This paper critiques the epistemic and structural failures of contemporary large language models and introduces the ESSIM AI Model-a principled architecture built on Epistemic Stratification, Semantic Integration, and Moral Reasoning.... more
Today advancements in information technology have led to multiuser information systems of high complexity, where users can group, collaborate and share resources. The variety of such systems include a wide range of applications such as... more
Background: The Ministry of Health of Malaysia has invested significant resources to implement an electronic health record (EHR) system to ensure the full automation of hospitals for coordinated care delivery. Thus, evaluating whether the... more
This report explores the integration of collaborative Artificial Intelligence (AI) in multi-hospital disease risk assessment preserving patient's data confidentiality, this report examines this integration. Hospitals can train... more
Properly managing healthcare data is a complex endeavor that must balance the requirements and interests of many stakeholders. In this paper, we present the findings from a panel discussion with healthcare professionals and academics, who... more
Healthcare decision-making has become increasingly complex due to the growing volume of patient and operational data. This paper explores unified architectures combining cloud technologies, data warehousing, and predictive database... more
This study explores mental health professionals' attitudes toward integrating artificial intelligence (AI) in psychosocial counseling. Using a quantitative survey approach, we examine variables such as perceived utility, comfort with AI... more
This white paper presents actionable strategies for reducing healthcare costs in the United States, integrating policy reform, technology adoption, and care delivery innovation. It reflects over 15 years of the author's professional... more
Artificial Intelligence (AI) has emerged as a transformative force within the healthcare sector, offering unprecedented advancements in clinical diagnostics, predictive analytics, and personalised medicine. The ability of AI systems to... more
The field of complementary and alternative medicine (CAM) has seen a surge in popularity as patients increasingly seek holistic and personalized healthcare.(Smith & Kalra, 2008) However, the integration of CAM practices has been hindered... more
This paper explores the optimization of healthcare management systems using Artificial Intelligence (AI) and Machine Learning (ML). As the complexity of healthcare systems continues to grow, AI and ML have emerged as key tools to improve... more
With continued advancements in wearable technologies, the applications for their use are growing. Wearable sensors can be found in smart watches, fitness trackers, and even our cellphones. The common applications in everyday life are... more
The quest for improved healthcare practice has directed several establishments to consider various processes, such as the initiation of human resource information systems (HRIS). Ideally, to realise the sustainable development goal (SDG... more
Cloud migration in the healthcare industry involves high-stakes initiatives impacting not only technical infrastructure but crucially data governance, compliance, and patient care. While public cloud platforms offer significant... more
The pharmaceutical industry has grown over the past decade especially with the embracing of technology in major parts of their operations. This dependence on the technology aspects has also resulted in increased vulnerability from attacks... more