Papers by Parag Chatterjee
Healthcare Through Data Science – A Transdisciplinary Perspective from Latin America
The Internet of Things : Foundation for Smart Cities, eHealth, and Ubiquitous Computing
Chapman and Hall/CRC eBooks, Oct 16, 2017
5G and Beyond
Chapman and Hall/CRC eBooks, May 9, 2022
Special Issue: IoT Toward COVID-19
Internet of Things, 2022
F1000Research
Artificial Intelligence (AI) and machine learning are the current forefront of computer science a... more Artificial Intelligence (AI) and machine learning are the current forefront of computer science and technology. AI and related sub-disciplines, including machine learning, are essential technologies which have enabled the widespread use of smart technology, such as smart phones, smart home appliances and even electric toothbrushes. It is AI that allows the devices used day-to-day across people’s personal lives, working lives and in industry to better anticipate and respond to our needs. However, the use of AI technology comes with a range of ethical questions – including issues around privacy, security, reliability, copyright/plagiarism and whether AI is capable of independent, conscious thought. We have seen several issues related to racial and sexual bias in AI in the recent times, putting the reliability of AI in question. Many of these issues have been brought to the forefront of cultural awareness in late 2022, early 2023, with the rise of AI art programs (and the copyright iss...
Predictive Modeling Toward the Design of a Forensic Decision Support System Using Cheiloscopy for Identification from Lip Prints
Communications in computer and information science, 2022
The European Physical Journal Plus
The global crisis related to the reduction of energy fossil resources, the reduction of potable w... more The global crisis related to the reduction of energy fossil resources, the reduction of potable water resources, and the war for the control of energy sources is part of some of the causes which can lead to an intentional CBRNe (Chemical, Biological, Radiological, Nuclear, and explosive) event. These kinds of events could also be the consequence of an intentional or unintentional release of substances (i.e., an accident of a truck containing a Toxic Industrial Chemical), or of natural events like a tsunami or an earthquake. Especially in today's global scenario, a sharp rise in the potential risks puts seminal importance on the development of new solutions to prevent such events, handle emergency situations and restore normalcy. The focus point is "New Technologies for Detection, Protection, Decontamination and Developments of the Decision Support Systems in Case of CBRNe Events" host some of the most innovative works presented during the second edition of the conference SICC Series-CBRNe Conference 2020 held in the virtual platform in December 2020 (https://www.sicc-series.com/). The major impact, in the papers selected for this focus point, is constituted by research on radiological and nuclear events (RN). The authors have published work on these main areas: • Detection and Identification Yale University and the University of Pisa developed an active interrogation system based on detectors containing liquid droplets that vaporize when exposed to fast neutrons but are insensitive to X-rays. With this system, it is possible to detect a sample of natural uranium either uncovered or shielded under heavy loads of wood or steel pipes which is an important application for the detection of special nuclear materials hidden in shipping containers [1]. The University of Sergipe and the University of Pisa have presented research that shows the potential of Allium cepa as a sensitive support system for dosimetry, detection, and screening of cellular effects produced by low doses of environmental radiation [2]. ENEA Casaccia Research Centre has developed a spectrometric monitoring method, based on a portable HpGe detector Trans-Spec-DX-100 for the fast screen of the contamination of a large number of individuals involved in a RN emergency [3]. University of Rome Tor Vergata and the Department of Italian Firefighters analyze the case study of the recovery of an orphan source of 60Co inside a maritime cargo full of metal wastes in the Italian Harbor of Genova [4]. The University of Pisa and the University of Rome Tor Vergata developed a prototype of a gamma ray detection and spectroscopy system based on affordable and commercially available technologies [5]. • Numerical methods and simulations University of Rome Tor Vergata evaluated the imaging performance of a novel muon tomography scanner based on resistive plate chamber detectors through Monte Carlo simulations [6]. ENEA and the University of Rome Tor Vergata developed a model mixing and transport of radioactive effluents in the course of time between two water reservoirs to estimate the amount of radioactivity concentration in both water reservoirs at any time, information that can be used for radiation protection purposes [7].
Cheiloscopy is a forensic investigation technique that deals with identification of humans based ... more Cheiloscopy is a forensic investigation technique that deals with identification of humans based on lips traces. Lip traces hold multifarious features and could be analyzed in different ways to identify the links with personal identifying features. Machine Learning holds strong application in this domain, especially for pattern recognition and further interpretation. This work is focused on a brief survey of existing machine learning approaches in Cheiloscopy. Also, a comparative study of predictive models has been presented based on an original dataset of lip prints where supervised models have been used to predict the biological sex of the persons using their lip traces. Machine learning on one hand automatizes the identification process and poses a significant potential in analyzing huge number of lip traces with considerable accuracy.
Device for the Evaluation of Carotid Arterial Pressure Based on IoT and 3D-Printing: uFISIO
Revista Argentina de Bioingeniería, Apr 23, 2020
Journal of advanced research in dynamical and control systems, Mar 31, 2020
Atrial fibrillation is a disorder in which there is a chaotic fire of electrical signals from the... more Atrial fibrillation is a disorder in which there is a chaotic fire of electrical signals from the upper chambers of the heart. The identification of the location of the myocardium responsible for firing these signals and ablation of the area may potentially cure the problem. The electrophysiologists may have to insert the probes or catheters and do the cardiac mapping to identify and analyze the complex heart signals patterns and to identify the location of AF responsible electrical foci. Nowadays, machine learning has become crucial in every technology field. Automation with software using machine-learning algorithms may aid electrophysiologists to do cardiac mapping without struggle and detecting electrical foci by computers. ML algorithms may identify arrhythmia compared to a board-certified cardiologist and can be developed as a very fast and reliable diagnostic tool.
Internet of Things for Ubiquitous Healthcare Services – Redefining eHealth
Internet of Things for Ubiquitous and Smart Healthcare Systems
Survey: Departamento de Ingeniería Biológica, Universidad de la República Uruguay (Course: Taller 1 — Change to Virtual Modality during COVID-19)
The dataset links to the survey performed on students and professors of Biological Engineering in... more The dataset links to the survey performed on students and professors of Biological Engineering introductory course, as the Department of Biological Engineering, University of the Republic, Uruguay.
Survey (Course: Taller de Ingeniería Biológica 1) Change to Virtual Modality during COVID-19
The dataset links to the survey performed on students and professors of Biological Engineering in... more The dataset links to the survey performed on students and professors of Biological Engineering introductory course, as the Department of Biological Engineering, University of the Republic, Uruguay.
Predictive Cardiometabolic Risk Profiling of Patients Using Vascular Age in Liver Transplantation
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Applied Approach to Privacy and Security for the Internet of Things
From transportation to healthcare, IoT has been heavily implemented into practically every profes... more From transportation to healthcare, IoT has been heavily implemented into practically every professional industry, making these systems highly susceptible to security breaches. Because IoT connects not just devices but also people and other entities, every component of an IoT system remains vulnerable to attacks from hackers and other unauthorized units. This clearly portrays the importance of security and privacy in IoT, which should be strong enough to keep the entire platform and stakeholders secure and smooth enough to not disrupt the lucid flow of communication among IoT entities. Applied Approach to Privacy and Security for the Internet of Things is a collection of innovative research on the methods and applied aspects of security in IoT-based systems by discussing core concepts and studying real-life scenarios. While highlighting topics including malware propagation, smart home vulnerabilities, and bio-sensor safety, this book is ideally designed for security analysts, softwar...
The Internet of Things The Internet of Things
Predictive Risk Analysis for Liver Transplant Patients - eHealth Model Under National Liver Transplant Program, Uruguay
2019 IEEE 9th International Conference on Advanced Computing (IACC), 2019
Recent years have seen a phenomenal change in healthcare paradigms and data analytics clubbed wit... more Recent years have seen a phenomenal change in healthcare paradigms and data analytics clubbed with computational intelligence has been a key player in this field. One of the main objectives of incorporating computational intelligence in healthcare analytics is to obtain better insights about the patients and proffer more efficient treatment. This work is based on liver transplant patients under the National Liver Transplant Program of Uruguay, considering in detail the health parameters of the patients. Applying computational intelligence helped to separate the cohort into clusters, thereby facilitating the efficient risk-group analysis of the patients assessed under the liver transplantation program with respect to their corresponding health parameters, in a predictive pre-transplant perspective. Also this marks the foundation of Clinical Decision Support Systems in liver transplantation, which act as an assistive tool for the medical personnel in getting a deeper insight to patien...
IoT-Based eHealth Toward Decision Support System for CBRNE Events
Recent years have seen a phenomenal change in healthcare paradigms, and Internet of Things (IoT) ... more Recent years have seen a phenomenal change in healthcare paradigms, and Internet of Things (IoT) clubbed with data analytics has been a key player in this field. IoT provides a common platform for seamless exchange between health devices and all the stakeholders of healthcare followed by advanced analysis of the shared pool of data. Clinical decision support system is an important component of the recent eHealth systems which acts as an assistive tool for the medical personnel in getting a deeper insight to patients’ health data and to design more efficient and personalized treatment strategy. Such a fascinating platform of IoT also finds use with respect to CBRNE; especially after a CBRNE event, such eHealth-based decision support system counts significant to guide the medical personnel in treating people. Moreover, having the comprehensive health profile of the mass enables the stakeholders to analyze and identify the potential risk groups, which would enhance the efficiency of tr...
IoT toward Efficient Analysis of Aging, Cardiometabolic, and Neurodegenerative Diseases—An eHealth Perspective
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Papers by Parag Chatterjee