Principles And Methods Of Explainable Artificial Intelligence In Healthcare

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Principles and Methods of Explainable Artificial Intelligence in Healthcare

Principles and Methods of Explainable Artificial Intelligence in Healthcare
Author :
Publisher : IGI Global
Total Pages : 347
Release :
ISBN-10 : 9781668437926
ISBN-13 : 1668437929
Rating : 4/5 (929 Downloads)

Book Synopsis Principles and Methods of Explainable Artificial Intelligence in Healthcare by : Albuquerque, Victor Hugo C. de

Download or read book Principles and Methods of Explainable Artificial Intelligence in Healthcare written by Albuquerque, Victor Hugo C. de and published by IGI Global. This book was released on 2022-05-20 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explainable artificial intelligence is proficient in operating and analyzing the unconstrainted environment in fields like robotic medicine, robotic treatment, and robotic surgery, which rely on computational vision for analyzing complex situations. Explainable artificial intelligence is a well-structured customizable technology that makes it possible to generate promising unbiased outcomes. The model’s adaptability facilitates the management of heterogeneous healthcare data and the visualization of biological structures through virtual reality. Explainable artificial intelligence has newfound applications in the healthcare industry, such as clinical trial matching, continuous healthcare monitoring, probabilistic evolutions, and evidence-based mechanisms. Principles and Methods of Explainable Artificial Intelligence in Healthcare discusses explainable artificial intelligence and its applications in healthcare, providing a broad overview of state-of-the-art approaches for accurate analysis and diagnosis. The book also encompasses computational vision processing techniques that handle complex data like physiological information, electronic healthcare records, and medical imaging data that assist in earlier prediction. Covering topics such as neural networks and disease detection, this reference work is ideal for industry professionals, practitioners, academicians, researchers, scholars, instructors, and students.


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