
Machine Learning, Medical AI and Robotics
Description
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Medical AI and Robotics are rapidly expanding fields nearing a point of maturity for clinical translation. However, there are still several issues that need to be addressed to overcome obstacles in clinical adoption. Much of the research has focused on proof of concept and limited experimental studies, which have shown promising results in medical artificial intelligence and robotics applications. However, there has been little effort to address the clinical translation of these technologies.
This book explores the latest advancements in medical technology, specifically focusing on artificial intelligence (AI) and robotics. It highlights how these breakthroughs are transforming the healthcare landscape and shaping the future of medicine.
The goal of this book is to provide a multidisciplinary perspective from experts in various medical subspecialties, examining the current and potential applications of medical AI and robotics. The authors guide readers through cutting-edge research and real-world examples, demonstrating how AI is revolutionizing disease diagnosis, drug discovery, personalized treatment plans, and prevention. It also discusses emerging technologies like wearables and showcases the emergence of medical robots that assist in complex surgeries and provide patient care.
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Persons
> 90 peer-reviewed articles, inventor of a few patents, and is a co-founder of a medical longevity startup, Snowhill Science Ltd. He is passionate about using technology in education.
>11) awards in international conferences/journals.
Jason Ying Kuen Chan is an Associate Clinical Professor at the Chinese University of Hong Kong and a Deputy Director of the CUHK Jockey Club Minimally Invasive Surgical Skills Centre. His research interests centre around the application of robotics in minimally invasive surgery and the role of the microbiome in head and neck cancers, with over 83 referred journal articles, 10 book chapters and 44 conference abstracts.
Qui Dou, is an Assistant Professor in the Department of Computer Science at the Chinese University of Hong Kong. Her research interest lies in the interdisciplinary area of AI for healthcare with expertise in medical image analysis and robot-assisted surgery towards the goal of advancing disease diagnosis and intervention via machine intelligence.
Content
Preface
Acknowledgements
Editor biographies
List of contributors
1 Machine learning in medicine-focus on radiology
2 Machine learning: applications in ophthalmology
3 Artificial intelligence clinical applications of wearable technologies
4 Artificial intelligence in dentistry and oral health
5 Artificial intelligence applications in pathology
6 Artificial intelligence-powered imaging-based diagnostic tools for ageing and longevity
7 Intra-operative image-guided interventional robotics-where are we now and where are we going?
8 Surgical applications in medical artificial intelligence
9 Technical innovations to improve artificial intelligence generalizability of automated medical image diagnosis for clinical practice
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