Explainable AI in Health Informatics (2024) (Computational Intelligence Methods and Applications)

By: Rajanikanth Aluvalu and Mayuri Mehta and Patrick Siarry

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Synopsis: This book provides a comprehensive review of the latest research in the area of explainable artificial intelligence (XAI) in health informatics. It focuses on how explainable AI models can work together with humans to assist them in decision-making, leading to improved diagnosis and prognosis in healthcare. This book includes a collection of techniques and systems of XAI in health informatics and gives a wider perspective about the impact created by them. The book covers the different aspects, such as robotics, informatics, drugs, patients, etc., related to XAI in healthcare. The book is suitable for both beginners and advanced AI practitioners, including students, academicians, researchers, and industry professionals. It serves as an excellent reference for undergraduate and graduate-level courses on AI for medicine/healthcare or XAI for medicine/healthcare. Medical institutions can also utilize this book as reference material and provide tutorials to medical professionals on how the XAI techniques can contribute to trustworthy diagnosis and prediction of the diseases.

Book Quality:: Publisher Quality
ISBN-13:: 9789819737055
Related ISBNs:: 9789819737048
Publisher:: Springer Nature Singapore
Date of Addition:: 08/08/24
Copyrighted By:: The Editor
Adult content:: No
Language:: English
Has Image Descriptions:: No
Categories:: Nonfiction, Science, Computers and Internet, Technology, Medicine
Submitted By:: Bookshare Staff
Usage Restrictions:: This is a copyrighted book.
Edited by:: Rajanikanth Aluvalu
Edited by:: Mayuri Mehta
Edited by:: Patrick Siarry