Machine Learning and Artificial Intelligence in Implantable Pacemaker Technology for Intelligent Cardiovascular Health
Dr. P. Janardhan Saikumar
Indexed In: google scholar
Release Date: 20/08/2025 | Copyright:©2025 | Pages: 384
DOI: 10.71443/9789349552586
ISBN10: 9349552582 | ISBN13: 9789349552586
Machine Learning and Artificial Intelligence in Implantable Pacemaker Technology for Intelligent Cardiovascular Health' explores the convergence of advanced machine learning algorithms and AI technologies with the design and functionality of implantable pacemakers. This book delves into how intelligent systems can optimize pacemaker performance, predict arrhythmias, and adapt to individual patient needs in real-time. It highlights cutting-edge innovations in AI-driven diagnostics, personalized care, and the future of cardiovascular health management, offering a comprehensive guide for healthcare professionals, engineers, and researchers working on the integration of AI into medical devices for improved patient outcomes.
This book bridges the gap between cutting-edge artificial intelligence and machine learning technologies and the evolving field of implantable pacemaker devices. It covers the design, development, and implementation of AI-driven algorithms that enable pacemakers to adapt to patients' unique cardiovascular conditions, ensuring more personalized and efficient care. It explores the challenges, opportunities, and ethical considerations of integrating AI in medical devices, along with potential advancements in predictive modeling, data-driven insights, and real-time diagnostics. A must-read for engineers, clinicians, and researchers eager to understand the future of intelligent cardiac healthcare.
Dr. P. Janardhan Saikumar, M.Tech, Ph.D., is a Professor in the Department of Electronics and Communication Engineering at Audisankara College of Engineering and Technology, Gudur, Andhra Pradesh. He holds B.Tech, M.Tech, and Ph.D. degrees in Electronics and Communication Engineering from Sri Venkateswara University College of Engineering (SVUCE), S.V. University, Tirupati. He has over five years of industry experience, including his role as a Process Automation Engineer at Lehman Brothers, London, and 3.5 years of research experience in Atmospheric Remote Sensing and Advanced Signal Processing at the Centre of Excellence under TEQIP-II 1.2.1 at SVUCE, S.V. University, Tirupati. With more than 12 years of teaching experience, his areas of expertise include Artificial Intelligence and Machine Learning, Deep Learning, Internet of Things (IoT), Biomedical Instrumentation, Image Processing, and Wireless Sensor Networks. He has published over 25 research papers in reputed national and international journals, presented more than 15 papers at various conferences, and has published 9 patents.