Transforming Healthcare

This book comprehensively discusses the latest trends and developments in healthcare applications, including artificial intelligence, the Internet of Things, machine learning algorithms, deep learning algorithms, and 5G technology. It covers important topics such as 5G-based smart healthcare network security, as well as data management and security. Features: . Covers the key challenges and considerations in healthcare applications and 5G technology, including safety, reliability, and cost-effectiveness. . Discusses the latest trends and developments in healthcare applications including artificial intelligence, the Internet of Things, and machine learning algorithms. . Provides an in-depth analysis of the technical aspects of 5G technology, healthcare automation, and the social and economic implications of the latest technologies. . Bridges the gap between artificial intelligence, machine learning, and deep learning with advanced communication technologies used in healthcare applications. . Highlights the latest design and problem-solving skills of engineering with health sciences to advance healthcare treatment using 5G technology. It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electrical and communications engineering, computer science and engineering, and biomedical engineering.

K.Srinivasan received his Bachelor's degree in Electronics and Communication Engineering from VLB Janakiammal College of Engineering and Technology, Coimbatore and ME in Process Control and Instrumentation Engineering from Annamalai University, Chidambaram in 1996 and 2004 respectively. He completed his Ph.D degree from Anna University, Chennai in 2012 under the faculty of Electrical Engineering. He has 24 years of experience in the field of Electronics, Communication, Instrumentation and Image & video processing. Presently, he is working as Professor and Head in the Department of Electronics and Instrumentation Engineering. Jude Hemanth received his B.E degree in ECE from Bharathiar University in 2002, M.E degree in communication systems from Anna University in 2006 and Ph.D. from Karunya University in 2013. His research areas include Computational Intelligence and Image processing. He has authored more than 310 research papers in reputed SCIE indexed International Journals and Scopus indexed International Conferences. Currently, he is working as Professor in Department of ECE, Karunya University, Coimbatore, India. V.Rukkumani is working as an Associate Professor in the Department of Electronics and Instrumentation Engineering at Sri Ramakrishna Engineering College, Coimbatore. She received her B.E degree in EIE from Bharathiar University in 2004, M.E degree in VLSI Design from Anna University in 2009 and Ph.D in Electrical Engineering in 2015. She has more than 20 years of experience in teaching. Her research interests include VLSI Design, Transducers and Industrial Instrumentation. She has published 45 technical papers in International Journals, 13 International Conferences and 15 National Conferences.

Chapter 1. Role of AI & ML in Lung Disease Detection based on Lung Sound Analysis using Deep Learning Algorithms. Chapter 2. Application of Artificial Intelligence (AI) for Tele-Healthcare System. Chapter 3. Transformative Applications of AI and ML in Diagnostics and Disease Treatment. Chapter 4. Predictions of Malnutrition among Children. Chapter 5. Precise segmentation of anterior cruciate ligament tear from clinical MR images using meta-heuristic optimization. Chapter 6. Design and Development of IoT-enabled Drone for Agriculture and Medical Applications with integration of AI. Chapter 7. A Deep Learning-based Diabetic Retinopathy Detection Model. Chapter 8. Building Network Slice for Health Care Equipment Over 5G Services. Chapter 9. Design and Implementation of Personal Protective Equipment Detection System using YOLO v9 for Industrial Environments. Chapter 10. Improving Spectrum Resource Management with an Advanced Deep Learning-based Model. Chapter 11. Hybrid Dense Block convolutional Transformers (DBCT) for Lung cancer detection and Severity Analysis. Chapter 12. Computer Vision-based Robotic Hand for Medical Healthcare Applications. Chapter 13. Yoga pose estimation using PoseNet Model. Chapter 14. Patient Health Monitoring using IoT and Machine Learning. Chapter 15. Leveraging Machine Learning and Artificial Intelligence for Advanced Mobile Network Systems. Chapter 16. Transforming Patient Care: The Impact of 5G Technology on Telemedicine, Remote Monitoring, and Healthcare Delivery. Chapter 17. Revolutionizing Healthcare: The Role of Artificial Intelligence, 5G, Cloud Services, and Other Enabling Technologies. Chapter 18. Melanoma Skin Cancer Detection Using Hybrid Attention DCNN-BiLSTM Architecture