The book explores the intersection of AI, telehealth, and viral infections, discussing the role of AI in pandemics, telehealth services, viral diagnosis, and antiviral drug development. It explores the integration of AI into telehealth, predicting outbreaks and monitoring mutations. The book emphasizes patient-centric healthcare, highlighting AI's transformative potential in infectious diseases. It covers medical virology, bioinformatics, machine learning, and neural networks. AI enables streamlined workflows, improved patient care, and new research methodologies. It addresses challenges and tailored solutions for AI integration in telehealth.

It serves as a valuable resource for clinicians, physicians, virologists, researchers, and healthcare professionals seeking to navigate the evolving landscape of telehealth and harness the full potential of AI in transforming healthcare delivery.

Explores the intersection of AI and telehealth along with latest advancements and future possibilities Covers diverse fields like medical biology, data science & bioinformatics, providing an overview of AI in healthcare Navigates the ethical considerations & implementation challenges of integrating AI into telehealth effectively

Autorentext

Mr. Jyotir Moy Chatterjee is currently working as an Assistant Professor in the Department of CSE at Graphic Era (Deemed to be University) located in Dehradun, Uttarakhand, India. Additionally, he holds a position as an Assistant Professor (Visiting Faculty) in the Department of IT at Lord Buddha Education Foundation Kathmandu, Nepal, which is affiliated with the Asia Pacific University, Malaysia. Before these roles, he has served as an Assistant Professor and Program Leader for the B.Sc. IT program at Lord Buddha Education Foundation and as an Assistant Professor in the CSE department at GD-Rungta College of Engineering & Technology, affiliated with Chhattisgarh Swami Vivekananda Technical University in Bhilai, India. His academic journey includes earning an M. Tech degree in Computer Science & Engineering from Kalinga Institute of Industrial Technology (KIIT) in Bhubaneswar, Odisha in 2016, and a B. Tech degree in Computer Science & Engineering from Dr. MGR Educational & Research Institute in Maduravoyal, Chennai in 2013. In terms of his research interests, he has a strong focus on Machine Learning and Deep Learning.

Prof. Dr. R. Sujatha completed her Ph.D. degree at Vellore Institute of Technology, Vellore, India, in the area of data mining. She received her M.E. degree in Computer Science from Anna University, India, with ninth rank, and pursued a Master of Financial Management from Pondicherry University, India. She received her B.E. degree in Computer Science from Madras University, India. She has 20 years of teaching experience and has been serving as an associate professor in the School of Computer Science Engineering and Information Systems at Vellore Institute of Technology, Vellore. Also serving as Assistant Director (Students' Welfare). She has organized and attended several workshops and faculty development programs. She actively involves herself in the growth of the institute by contributing to various committees at both academic and administrative levels. She used to guide projects for undergraduate and postgraduate students and currently guides doctoral students. She gives technical talks in colleges for symposiums and various sessions. She acts as an advisory, editorial, and technical committee member in conferences conducted in other educational institutions and in-house. She has published a book titled Software Project Management for College Students. She has published research articles in reputed high-impact journals and can find 80 articles in Google Scholar, 20 book chapters, 3 edited, and 2 authored books. The Institution of Green Engineers awarded her IGEN Women Achiever 2021 award in the Future Computing category. Outstanding Researcher Awardee for the year 2022 was awarded by VIT. She is interested in exploring and visiting different places to learn about the culture and people of various areas. She is interested in learning upcoming things and gets acquainted with the student's level. Her areas of research interest include Information Management and Data Analytics, Artificial Intelligence, Soft Computing, Medical AI, Big Data, Deep Learning, and Blockchain Software Engineering.

Professor (Dr.) Shailendra K. Saxena is vice dean and professor at King George's Medical University, Lucknow, India. His research interests are to understand the molecular mechanisms of host defense during human viral infections and to develop new predictive, preventive, and therapeutic strategies for them using emerging and re-emerging viruses as a model, via stem cell and cell culture technologies. His research work has been published in various high-impact factor journals (Science, PNAS, Nature Medicine) with high citations. He has received many awards and honors in India and abroad including various Young Scientist Awards, the BBSRC India Partnering Award (UK), Dr. JC Bose National Award of the Department of Biotechnology, Min. of Science and Technology, Govt. of India, and Fellow of various internationally prestigious societies/academies including The Royal College of Pathologists (UK), Royal Societies of Biology and Chemistry, London, United Kingdom, Academy of Translational Medicine Professionals, Austria, Indian Virological Society, and is named as the Global Leader in Science by The Scientist magazine (USA) and International Opinion Leader/Expert involved in the vaccination for JE by IPIC (UK).

Inhalt

Chapter 1. Transforming Healthcare: The Synergy of Telemedicine, Telehealth, and Artificial Intelligence.- Chapter 2. Role of AI in diagnosis of Viral Infection.- Chapter 3. The Influence of Artificial Intelligence in Drug Discovery and Development.- Chapter 4. Transformative effect on the role of telehealth during pandemic.- Chapter 5. Effective Cloud Infrastructure for Optimal Telehealth Service.- Chapter 6. Advancements of Telemedicine using Blockchain and Deep Learning for Smart Healthcare.- Chapter 7. Impact of Telehealth during Pandemic in Remote Locations.- Chapter 8. A Terrific Structure for City Dengue Predictive Recommender Analytics.- Chapter 9. Machine Learning for Intelligent Healthcare Across Decentralized Patient Databases Using Federated Learning.- Chapter 10. Cancer Disease Prediction Using an Integrated Ensemble Technique with ReliefF and FP.- Chapter 11. AI Managed Hospital Workforce.- Chapter 12. Healthcare Data Security in Multi-Cloud Infrastructure using Heuristic Algorithms.