Deep Learning in Cardiovascular Health (eBook)

Sustainable Al Approaches for Heart Disease Diagnosis and Treatment
Artikelnummer: 978-3-032-12470-8
Einband: PDF
Verfügbarkeit: Download, sofort verfügbar (Link per E-Mail)
CHF 236.00
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This book showcases the most recent developments in the application of artificial intelligence to cardiology and medical imaging, with an emphasis on precise diagnosis, early prediction, and patient-centered care. In order to overcome clinical data ambiguity and enhance confidence in automated systems, it presents innovative frameworks that combine deep learning, fuzzy graph neural networks, metaheuristic optimization, and explainable AI. This book bridges the gap between state-of-the-art research and practical healthcare applications by covering a wide range of techniques, including CNNs, RNNs, residual networks, federated learning, and multimodal learning. As a research reference and a manual for implementing AI-driven healthcare solutions, it provides useful tools, datasets, and methodologies that foster innovation in precision medicine and medical decision-making. It is designed for researchers, clinicians, and students.

This book showcases the most recent developments in the application of artificial intelligence to cardiology and medical imaging, with an emphasis on precise diagnosis, early prediction, and patient-centered care. In order to overcome clinical data ambiguity and enhance confidence in automated systems, it presents innovative frameworks that combine deep learning, fuzzy graph neural networks, metaheuristic optimization, and explainable AI. This book bridges the gap between state-of-the-art research and practical healthcare applications by covering a wide range of techniques, including CNNs, RNNs, residual networks, federated learning, and multimodal learning. As a research reference and a manual for implementing AI-driven healthcare solutions, it provides useful tools, datasets, and methodologies that foster innovation in precision medicine and medical decision-making. It is designed for researchers, clinicians, and students.

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VerlagSpringer Nature Switzerland
EinbandPDF
Erscheinungsjahr2026
Seitenangabe260 S.
AusgabekennzeichenEnglisch
AbbildungenXIII, 260 p. 69 illus., 57 illus. in color.
Masse13'183 KB
PlattformPDF
ReiheInformation Systems Engineering and Management; Medicine; Medicine
AutorNag, Anindya (Hrsg.) / Hassan, Md. Mehedi (Hrsg.) / Bairagi, Anupam Kumar (Hrsg.)

Alle Bände der Reihe "Information Systems Engineering and Management; Medicine; Medicine (R0)"

Über den Autor Anindya (Hrsg.) Nag

Anindya Nag obtained an M.Sc. in Computer Science and Engineering from Khulna University in Khulna, Bangladesh, and a B.Tech. in Computer Science and Engineering from Adamas University in Kolkata, India. He is currently a lecturer in the Department of Computer Science and Engineering at the Northern University of Business and Technology in Khulna, Khulna 9100, Bangladesh. His research focuses on health informatics, medical Internet of Things, neuroscience, and machine learning. He serves as a reviewer for numerous prestigious journals and international conferences. He has authored and co-authored about 60 publications, including journal articles, conference papers, and book chapters, and has co-edited books.Md. Mehedi Hassan is currently a Ph.D. researcher in STEM (Computer and Information Science) at the University of South Australia, working on a fully funded research project. He started his Ph.D. in 2025, building on a strong academic background in computer science and engineering. He holds an M.Sc. in Computer Science and Engineering from Khulna University, Bangladesh, completed in 2024, and a B.Sc. in Computer Science and Engineering from North Western University, completed in 2022. His research spans computer science engineering and data science, with a strong focus on predictive analysis and expert system development. Md. Mehedi Hassan has authored 73 research papers and edited 5 books, actively contributing to the academic community. He serves as a peer reviewer for over 80 prestigious journals and collaborates extensively in interdisciplinary research. As a trainer for the VCourse platform, he has educated over 250 students over the past two years, sharing knowledge in emerging technologies and research methodologies. Beyond publications, he has actively engaged in intellectual property development, with several patents filed and three already granted in his name. His current research interests include computational neuroscience, machine learning for healthcare, and predictive modeling for biometrics.Dr. Riya Sil is an Associate Professor in Department of Computer Science & Engineering, Brainware University, Kolkata, India. Dr. Riya Sil holds a B.Tech & M.Tech degree in Computer Science & Engineering from Birla Institute of Technology and a PhD degree with a specialization in Legal Analytics. She has a total professional experience of about 9 years, including 7 years in academics and 2 years as Software Developer at Cognizant Technology Solutions (CTS). During her academic tenure, she has served as Asst. Professor in Computer Science & Engineering department in various institutions like Kristu Jayanti College - Autonomous, Techno India University, and Adamas University. Her research focuses on Machine Learning; Natural Language Processing (NLP); Deep Learning; Artificial Intelligence (AI) and Cloud Computing. She serves as a reviewer for various reputable journals and international conferences. She has about 40 publications to her credit which include peer-reviewed SCI and Scopus-indexed journals, conferences and book chapters.Dr. Asif Karim currently works at the Faculty of Science and Technology, Charles Darwin University. Asif does research in Machine Learning based Health Informatics and Blockchain Applications. He has considerable Industry Experience in the field of IT, primarily in Software Engineering. Complete Information about his Research Publications, Teaching and Grants are available at https://asifkarim.com/.

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