Biomedical Engineering

AI and Technological Innovations
2024
ISBN: 978-981-97-9293-1
Verlag: Springer Nature Singapore

Buch, Englisch, 163 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 434 g

Reihe: Series in BioEngineering

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.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Yeoh, Pauline Shan Qing

Lai, Khin Wee

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Signalverarbeitung
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Naturwissenschaften Physik Angewandte Physik Medizinische Physik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

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.

Über Autor(innen)

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.