UID:
almahu_9949747628802882
Format:
1 online resource.
Edition:
First edition.
ISBN:
9781003426073
,
1003426077
,
9781040020456
,
1040020453
,
9781040020449
,
1040020445
Series Statement:
Biomedical and robotics healthcare
Content:
"This book highlights the use of explainable artificial intelligence (XAI) for healthcare problems, in order to improve trustworthiness, performance and sustainability levels in the context of applications. Explainable Artificial Intelligence (XAI) in Healthcare adopts the understanding that AI solutions should not only have high accuracy performance, but also be transparent, understandable and reliable from the end user's perspective. The book discusses the techniques, frameworks, and tools to effectively implement XAI methodologies in critical problems of healthcare field. The authors offer different types of solutions, evaluation methods and metrics for XAI and reveal how the concept of explainability finds a response in target problem coverage. The authors examine the use of XAI in disease diagnosis, medical imaging, health tourism, precision medicine and even drug discovery. They also point out the importance of user perspectives and value of the data used in target problems. Finally, the authors also ensure a well-defined future perspective for advancing XAI in terms of healthcare. This book will offer great benefits to students at the undergraduate and graduate levels and researchers. The book will also be useful for industry professionals and clinicians who perform critical decision making tasks"--
Additional Edition:
Print version: Explainable artificial intelligence (XAI) in healthcare Boca Raton : CRC Press, 2024 ISBN 9781032543703
Language:
English
DOI:
10.1201/9781003426073
URL:
https://www.taylorfrancis.com/books/9781003426073
