The text presents concepts of explainable artificial intelligence
(XAI) in solving real world biomedical and healthcare problems. It
will serve as an ideal reference text for graduate students and
academic researchers in diverse fields of engineering including
electrical, electronics and communication, computer, and
biomedical. Present explainable artificial intelligence (XAI) based
machine analytics and deep learning in medical science. Discusses
explainable artificial intelligence (XA)I with the Internet of
Medical Things (IoMT) for healthcare applications. Covers
algorithms, tools, and frameworks for explainable artificial
intelligence on medical data. Explores the concepts of natural
language processing and explainable artificial intelligence (XAI)
on medical data processing. Discusses machine learning and deep
learning scalability models in healthcare systems. This text
focusses on data driven analysis and processing of advanced methods
and techniques with the help of explainable artificial intelligence
(XAI) algorithms. It covers machine learning, Internet of Things
(IoT), and deep learning algorithms based on XAI techniques for
medical data analysis and processing. The text will present
different dimensions of XAI based computational intelligence
applications. It will serve as an ideal reference text for graduate
students and academic researchers in the fields of electrical
engineering, electronics and communication engineering, computer
engineering, and biomedical engineering.
General
Imprint: |
Taylor & Francis
|
Country of origin: |
United Kingdom |
Series: |
Explainable AI XAI for Engineering Applications |
Release date: |
October 2023 |
First published: |
2024 |
Editors: |
Om Prakash Jena
• Utyunjaya Panda
• Utku Kose
|
Dimensions: |
234 x 156mm (L x W) |
Pages: |
288 |
ISBN-13: |
978-1-03-219112-6 |
Categories: |
Books
|
LSN: |
1-03-219112-0 |
Barcode: |
9781032191126 |
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