Since the AI in healthcare is a comparatively new field, there exists a vacuum of literature in this field, especially applied to COVID-19. The area of AI in COVID-19 being quite young, the students and researchers usually face a struggle to rely on few published papers (which are obviously too specific) or white-papers by tech-giants (which are too wide). Artificial Intelligence in Healthcare and COVID-19 bridges this gap and provide a comprehensive guide to the field, showcasing the theoretical concepts as well as the implementational and research perspectives of AI in healthcare to combat COVID-19.
Moreover, in the domain of Artificial Intelligence and COVID-19, a proper fusion of medical and technological perspectives is necessary, to create solutions in combating the pandemic issues. This book addresses this area by adding medical and technological visions at the same time, making it even more applied. With the advent of COVID-19, it is obvious that leading universities and medical schools need to include the topics and case studies of Artificial Intelligence in Healthcare and COVID-19 in their usual courses of health informatics, to keep up with the pace of technological and medical advancements. This book also serves professors teaching these courses. Also, there are industry practitioners and professionals, working in the R&D team of leading medical and informatics companies who are bound to embrace AI and eHealth to fight COVID-19. The lack of a comprehensive literature makes it a herculean task for them to get a one-stop holistic view of the field. This book will serve them too in a significant way.
- Discusses the fundamentals and theoretical concepts of applying AI in healthcare pertaining to COVID-19
- Provides a landscape view to the applied aspect of AI in healthcare related COVID-19 through case studies and innovative applications
- Discusses the key concerns, and challenges in the field of AI in eHealth during the pandemic, along with other allied fields like IoT, creating a broad platform of transdisciplinary discussion
1. Introduction
2. Technological solutions regarding mental health of frontline healthcare workers during COVID-19 pandemic using artifical intelligence
3. Effective algorithms for solving statistical problems posed by the COVID-19 andemic
4. Artifical intelligence to analyse pharmaceutical interventions for COVID-19
5. Covid-19: artificial intelligence solutions, prediction with country cluster analysis and time series forecasting
6. Graph convolutional networks for pain detection via telehealth
7. The role of social media in the battle against COVID-19
8. De-identification techniques to preserve privacy in medical record
9. Estimation of COVID-19 fatality associated to different SARS-CoV-2 variants
10. Artificial intelligence for segmenting CT chest imaging in the fight of COVID-19
Parag Chatterjee works as an Assistant Professor at the Department of Biological Engineering (Area of Informatics) in the University of the Republic (Universidad de la República), Uruguay and also as a Research Professor at National Technological University (Universidad Tecnológica Nacional) in Buenos Aires, Argentina. After graduating in Computer Science from University of Calcutta, India., currently he is working in the field of Internet of Things, especially in the aspects of eHealth, to research on the methodologies for better prevention of cardiometabolic diseases and aging. Chatterjee has authored several scientific papers, published in international journals and presented at international conferences. Senior Researcher, Institute for High Performance Computing and Networking (ICAR), National Research Council of Italy (CNR), Naples, Italy
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