IoT and AI-Enabled Healthcare Solutions for Intelligent Disease Prediction

1. Auflage 2025
ISBN: 978-1-032-82125-2
Verlag: Taylor & Francis Ltd

Buch, Englisch, 266 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 650 g

The book presents fundamental to advanced concepts of AI and IoT in healthcare and disease prediction, demonstrating the emerging mechanisms, including machine learning, deep learning, image sensing, and explainable AI models to handle issues in healthcare industries with real-life scenarios. Included chapters are contributed by experienced professionals and academicians who examine severe diseases, applications, models, tools, frameworks, case studies, applications, and best practices in Healthcare. This book integrates the medical domain with AI technology. It covers trending explainable AI, computer vision (CV), and IoT that facilitate automation for healthcare solutions and medical diagnostics. The primary focus on explainable AI uncovers the black box of deep learning and bridges the distance between medical professionals and technologists. IoT in Healthcare: provides a mechanism of image sensing and is helpful in surgical tools.

Zielgruppe

Academic and Postgraduate

Autoren/Hrsg.

Singh Bhati, Bhoopesh

Tiwari, Dimple

Singh Bhati, Nitesh

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Gesundheitswirtschaft
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

Preface. 1. Introduction to IoT and AI for Providing Healthcare Solutions. 2. Seeing Beyond Symptoms: Utilizing Machine Learning Techniques for Early Diabetes Diagnosis. 3. A Decent ML-Based System for Cardiovascular Disease Detection. 4. Breast Cancer Detection Using Explainable Artificial Intelligence. 5. Deep Learning Applications for Chronic Disease Detection and Prevention. 6. Glaucoma Detection Using Retinal Images Employing Machine Learning (ML) Algorithms. 7. Design and Development of Intelligent Systems for Skin Cancer Detection. 8. IoT Enabled System for Regulating Medical Efficiency and Healthcare Services. 9. Tumor Prediction Using MRI Images Employing Deep Neural Network. 10. Nanorobots in the Treatment of Cancer: A Revolutionizing and Precision Medicine With Advantages and Limitations. 11. Methods of Explainable AI for Continuum Blood Glucose Monitoring with Various Challenges and Future Research Direction. 12. IoT and AI-based Intelligent Management of Heart Rate Monitoring. 13. Brain Tumor Prediction using MRI Images Employing Convolutional Neural Network (CNN). 14. Decision Support System for Miscarriage Rate Prediction. Index.

Über Autor(innen)

Dr. Bhoopesh Singh Bhati is an Assistant Professor in Indian Institute of Information Technology Sonepat (Institution of National Importance) Under Ministry of Education, Government of India. He received his Ph.D. (Computer and Engineering) from the University School of Information Communication and Technology, Guru Gobind Singh Indraprastha University Delhi, in 2020. Dr. Bhati has published various research papers in highly reputed, SSCI/SCI/SCIE-indexed journals including Elsevier, Wiley, Springer, Inderscience, etc. He is a recognized/active reviewer for various reputed journals of IEEE, Elsevier, Wiley, Springer etc. Dr. Bhati has an h-index of 13 and an i10 index of 14.

Dr. Dimple Tiwari is an Assistant Professor at the School of Engineering & Technology, Vivekananda Institute of Professional Studies - Technical Campus, Delhi, India. She received her Ph.D. (Computer and Engineering) from the University School of Information Communication and Technology, Guru Gobind Singh Indraprastha University Delhi, in 2023. Dr. Tiwari has published various research papers in highly reputed, SSCI/SCI/SCIE-indexed journals including Elsevier, Wiley, Springer, Inder science, etc. She is a recognized/active reviewer for various reputed journals of IEEE, Elsevier, Wiley, Springer etc.

Dr. Nitesh Singh Bhati is an Assistant Professor in the School of ICT, Department of Computer Science and Engineering at Gautam Buddha University, Greater Noida, UP, India. He holds a B.Tech from UPTU Lucknow, M.Tech, and Ph.D. in Computer Science and Engineering from GGSIPU, New Delhi. He has more than 8 years of teaching experience. His research interests focus on Information Security, Machine Learning & Artificial Intelligence, where he has contributed to advancing knowledge and solutions in the field. He has published various research papers in reputed journals. Dr. Bhati is an active reviewer for various reputed journals, further enhancing his involvement in the academic community.