Overview

The book explores the application of artificial intelligence across various human-machine interfaces, addressing areas such as human attention, emotions, seizures, Alzheimer's disease, focal and non-focal disorders, electrocardiogram rhythms, abnormal heartbeats, and leukemia. It provides a thorough examination of techniques for analyzing and processing both physiological and physical signals, as well as smear blood images. Physiological signals discussed include electroencephalograms (EEG), electrocardiograms (ECG), and electronic health records (EHR), while physical signals encompass human speech. Serving as a comprehensive guide, the book delves into advanced signal processing techniques and the use of machine learning and deep learning for automated signal pre-processing and classification. Key Features Comprehensive review of the latest trends in physiological healthcare analytics for disease diagnostics In-depth analysis of healthcare and major clinical applications using state-of-the-art AI techniques Application of advanced and adaptive signal analysis methods for improved diagnostics Integration of AI and transfer learning applications in healthcare Contributions from highly cited researchers in their respective fields Chapter content includes summaries, objectives, outcomes, worked examples, and multimedia Extensive references are provided at the end of each chapter to support further research and study

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9780750359627

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Author Information

Smith Khare is an Assistant Professor in the SDU Applied AI and Data Science, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Denmark, and worked as a Postdoctoral researcher in the Aarhus University, Denmark. He received his doctoral degree in Electronics and Communication Engineering at the Indian Institute of Information Technology, Design and Manufacturing Jabalpur (IIITDMJ), India in 2022. He has authored more than 50+ research papers in various reputed international Journals such as IEEE Transactions. Smith is listed in the top 2% Scientist in the World (2023, 2024), according to Elsevier. Sachin Taran is an Assistant Professor in the Department of Electronics and Communication Engineering at Delhi Technical University, New Delhi, India. He has done postdoc research at the Nanyang Technological University (NTU) Singapore. His research interests include artificial intelligence, signal processing and time-frequency analysis. He is a fellow member of IETE, member of IANG and Associate Editor of Frontiers in Signal Processing. Since 2020, he has continuously awarded by Commendable Research Award in Delhi Technological University. He has authored more than 55+ research papers in various reputed international Journals and conferences. Ankush D. Jamthikar is a postdoctoral research associate in the Division of Cardiovascular Disease and Hypertension at Rutgers University, Robert Wood Johnson Medical School, New Jersey. He has authored over 50 international journal papers, conference proceedings, and book chapters, focusing on cardiovascular disease (CVD) and stroke risk stratification, as well as artificial intelligence. He serves as an editorial board member for AI in Health and a guest editor for the MDPI journal, while also acting as a peer reviewer for several high-impact journals. Jamthikar has an h-index of 24 and an i-index of 34, with over 1,300 citations to his work.

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