The Impact of Algorithmic Technologies on Healthcare (Machine Learning in Biomedical Science and Healthcare Informatics)

The book explores the fundamental principles and transformative advancements in cutting-edge algorithmic technologies, detailing their application and impact on revolutionizing healthcare.

This book provides an in-depth account of how technologies such as artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) are reshaping healthcare, transitioning from traditional diagnostic and treatment approaches to data-driven solutions that improve predictive accuracy and patient outcomes. The text also addresses the challenges and considerations associated with adopting these technologies, including ethical implications, data security concerns, and the need for human-centered approaches in algorithmic medicine.

After introducing digital twin technology and its potential to enhance healthcare delivery, the book examines the broader effects of digital technology on the healthcare system. Subsequent chapters explore topics such as innovations in medical imaging, predictive analytics for improved patient outcomes, and deep learning algorithms for brain tumor detection. Other topics include generative adversarial networks (GANs), convolutional neural networks (CNNs), smart wearables for remote patient monitoring, effective IoT solutions, telemedicine advancements, and blockchain security for healthcare systems. The integration of biometric systems driven by AI, securing cyber-physical systems in healthcare, and digitizing wellness through electronic health records (EHRs) and electronic medical records (EMRs) are also discussed. The book concludes with an extensive case study comparing the impacts of various healthcare applications, offering insights and encouraging further research and innovation in this dynamic field.

Audience

This book is suitable for academicians and professionals in health informatics, bioinformatics, biomedical science and engineering, artificial intelligence, as well as clinicians, IT specialists, and policymakers in healthcare.

Parul Dubey, PhD, is an assistant professor in the Department of Artificial Intelligence, G. H. Raisoni College of Engineering, Nagpur, India. Her academic and research focus spans various areas of computer science and IT. She has published approximately 50 works, including journal articles, conference papers, and book chapters, along with 17 Indian patents.

Mangala Madankar, PhD, is the head of the Department of Artificial Intelligence at G. H. Raisoni College of Engineering, Nagpur, India. Her research interests include natural language processing, data science, big data, and information retrieval systems. She has published over 55 research papers in international journals and conferences.

Pushkar Dubey, PhD, is an assistant professor and head of the Department of Management at Pandit Sundarlal Sharma (Open) University, Chhattisgarh, Bilaspur. He has published more than 70 research papers in reputed journals, secured 7 patents, and completed 5 research projects.

Bui Thanh Hung, PhD, is affiliated with the Data Science Laboratory, Data Science Department, Faculty of Information Technology, Industrial University of Ho Chi Minh City, Vietnam. His research focuses on natural language processing, machine learning, machine translation, and text processing. He has published two books and approximately 40 conference papers.