This book brings together contributions from leading experts in the field, each addressing a critical area where AI and technology are making significant impacts. The chapters encompass a wide range of topics, from the application of machine learning in cancer grading and maternal health monitoring to the development of innovative wearable devices and advanced diagnostic tools. The book not only underscores the transformative potential of AI and technology in biomedical; but also serves as a vital resource for researchers, practitioners, and students. By showcasing the latest research and innovations, this book aims to inspire continued exploration and development in this dynamic and rapidly evolving field.

Provides an overview and offers insights into how AI and technology are transforming the landscape of modern medicine Brings together contributions from leading experts in the field, each addressing a critical area where AI & technology Serves as a vital resource for researchers, practitioners, and students

Autorentext

Dr. Khin Wee Lai obtained his PhD in Biomedical Engineering under DAAD PhD sandwich program between Technische Universität Ilmenau, Germany and Universiti Teknologi Malaysia, Johor Bahru. His research interests include medical imaging, 3D reconstruction and visualization, medical informatics and medical instrumentation. He is a professional member of ACM and he served as the member of board of editorial for a few international journals. Meanwhile, he is also the program committee and peer reviewer for over 20 international conferences.

Dr. Pauline Shan Qing Yeoh received the B.Eng. (Hons.) and PhD degrees from Universiti Malaya, Malaysia. She is currently a Postdoctoral Research Fellow with the Department of Biomedical Engineering, Faculty of Engineering, Universiti Malaya. Her research interests include artificial intelligence, image processing, medical imaging, and healthcare analytics.

Inhalt

Development of a Web-Based Maternal Health Monitoring System: Advancing Beyond Manual Record-keeping.- Development and Testing of a Home-based Phototherapy System for Neonatal Jaundice.- Non-Invasive Blood Glucose Monitoring Via Infrared Absorbance.- mpowering Predictive Maintenance of Medical Equipment through AI[1]Driven Condition Monitoring.- Multi-Label Convolutional Neural Network For Multiple Diseases Detection In Chest Radiographs.- Artificial Intelligence in Prosthetic Gait Assessment and Prosthesis Control: Present and Future.- Preliminary Analysis of Ultrasound Features for Detection of Polycystic Ovary Syndrome (PCOS) in Women.- Mechanomyography Analysis of Respiratory Muscle Function while Singing in Spinal Cord Injury.