This book comprehensively explores the latest technological advancements in healthcare, with a particular focus on the application of cutting-edge technologies, such as artificial intelligence (AI), computer vision, and robotics. The focus extends across crucial domains, such as disease diagnosis and monitoring, medical imaging, and the facilitation of remote healthcare services.
The book provides a comprehensive overview of AI techniques for intelligent diagnoses, discussing how machine learning and deep learning models enhance accuracy and speed in medical imaging, diagnostics, and patient care. It also delves into the integration of AI with other disciplines, such as data science, computer vision, edge computing, robotics, and web development, to tackle complex medical challenges. Moreover, it highlights current trends and future prospects in surgery, rehabilitation, neuroscience, and automated healthcare systems, offering valuable insights into the future of technology-driven healthcare solutions. The chapters are authored by researchers and professionals from every region of the globe, including Africa, Asia, the Americas, Europe, and Oceania. This global contribution highlights the versatility and broad perspectives of the shared insights and conclusions presented in the book.
This book is an essential guide for healthcare professionals, researchers, and enthusiasts eager to understand and actively contribute to shaping the future of healthcare through the integration of AI and other disciplines.
Table of Contents Series Editor Foreword Contributor Biographies 1. A Deep Learning Method for Identification of Pneumonia from Chest X-rays Debasish Borah, Amita Nandal and Arvind Dhaka 2. Recent Development and Applications of Deep Learning in Medical Imaging Olarenwaju James Awoniya, Vivens Mubonanyikuzo, Temitope Emmanuel Komolafe 3. How to Incorporate Prior Knowledge for Effective fMRI Data Analysis: A Comprehensive Review and Future Direction Yuhu Shi, Nizhuan Wang and Weiming Zeng 4. AI Applications in Diagnostics and Treatment Yuchi Tian, Temitope Emmanuel Komolafe and Wenxiu Zhang 5. eHealth Platforms Facilitate Breast Cancer: A Systematic Review Arpit Kumar Sharma, Arvind Dhaka and Amita Nandal 6. Rehabilitation and Assistive Robotics for the Elderly and Physically Challenged Marwa Mohammed 7. Surgical Robots for Minimally Invasive Surgery Li Liu and Yizhao Qian 8. AI-Aided Tools for Teaching and Research in Medical Research Charles Oretomiloye and Blessing Funmi Komolafe 9. Decoding Neural Signals: Invasive BMI Review Rezwan Firuzi, Ayub Bokani, Jahan Hassan, Hamed Ahmadyani, Mohammad Foad Abdi, Dana Naderi and Diako Ebrahimi 10. Real-time Healthcare Applications: Exploring the Synergy of Generative AI and Edge Computing/5G Mary Adedoyin 11. HealthSyncc: An AI-Powered Mobile Application for Health Management Ebenezer Juliet Selwyn, Anmol Tiwari, Gadewar Gayatri Pandurang, Sweta Soundarya Das and Raj Vardhan 12. Challenges and Future Trends in Implementing AI in Healthcare Adanze Nge Cynthia 13. The Future of AI in Healthcare: Opportunities and Challenges Olapeju A. Sam-Oyerinde, Oluwaremilekun O. Idowu and Oluwagbenga P. Idowu
Temitope Emmanuel Komolafe is an Assistant Professor at the Collaborative Research Centre, Shanghai University of Medicine and Health Sciences. His research focuses on intelligent medicine, medical imaging processing, and precision rehabilitation robotics. He has published many research articles in peer-reviewed international journals. Patrice Monkam is an Assistant Professor at Northeastern University, China. His research interests include image processing and analysis, medical imaging, and deep learning and its applications. He has authored over 20 research articles in leading peer-reviewed journals and at top-tier conferences. Blessing Funmi Komolafe is a Lecturer at the College of International Education, Shanghai University of Medicine and Health Sciences. Her research focuses on pre-service physics teacher training, curriculum, pedagogy, medical education, and AI-based teaching. She has published extensively in international journals. Nizhuan Wang is a Research Assistant Professor at the Hong Kong Polytechnic University, China. His research interests include brain-machine interface, neural computation, neuroimaging, neuroscience, and neurolinguistics. He has authored over 90 research articles in peer-reviewed top-tier journals and at conferences.