Explainable Artificial Intelligence for Medical Data Analytics and Healthcare Applications
Category: eBooks
- views: 153
- date: 16 July 2026
- posted by: BeMyLove
Explainable Artificial Intelligence for Medical Data Analytics and Healthcare Applications | 79.42 MB
Title: Explainable Artificial Intelligence for Medical Data Analytics and Healthcare Applications
Author: Ganesh R Naik
Category: Nonfiction, Science & Nature, Technology, Imaging Systems, Engineering, Computers, General Computing
Language: English | 322 Pages | ISBN: 9781003810605
Description:
Since its first appearance, artificial intelligence has been ensuring revolutionary outcomes in the context of real-world problems. At this point, it has strong relations with biomedical and today's intelligent systems compete with human capabilities in medical tasks. However, advanced use of artificial intelligence causes intelligent systems to be black-box. That situation is not good for building trustworthy intelligent systems in medical applications. For a remarkable amount of time, researchers have tried to solve the black-box issue by using modular additions, which have led to the rise of the term: interpretable artificial intelligence. As the literature matured (as a result of, in particular, deep learning), that term transformed into explainable artificial intelligence (XAI).
This book provides an essential edited work regarding the latest advancements in explainable artificial intelligence (XAI) for biomedical applications. It includes not only introductive perspectives but also applied touches and discussions regarding critical problems as well as future insights.
Topics discussed in the book include:
Explainable Artificial Intelligence for Biomedical Applications is ideal for academicians, researchers, students, engineers, and experts from the fields of computer science, biomedical, medical, and health sciences. It also welcomes all readers of different fields to be informed about use cases of XAI in black-box artificial intelligence. In this sense, the book can be used for both teaching and reference source purposes.
DOWNLOAD:
https://rapidgator.net/file/ee837ee7faa166a1fd1719759564e079/978-981-95-3811-9.rar
https://nitroflare.com/view/2265DE4FD9136B8/978-981-95-3811-9.rar
Since its first appearance, artificial intelligence has been ensuring revolutionary outcomes in the context of real-world problems. At this point, it has strong relations with biomedical and today's intelligent systems compete with human capabilities in medical tasks. However, advanced use of artificial intelligence causes intelligent systems to be black-box. That situation is not good for building trustworthy intelligent systems in medical applications. For a remarkable amount of time, researchers have tried to solve the black-box issue by using modular additions, which have led to the rise of the term: interpretable artificial intelligence. As the literature matured (as a result of, in particular, deep learning), that term transformed into explainable artificial intelligence (XAI).
This book provides an essential edited work regarding the latest advancements in explainable artificial intelligence (XAI) for biomedical applications. It includes not only introductive perspectives but also applied touches and discussions regarding critical problems as well as future insights.
Topics discussed in the book include:
- XAI for the applications with medical images
- XAI use cases for alternative medical data/task
- Different XAI methods for biomedical applications
- Reviews for the XAI research for critical biomedical problems.
Explainable Artificial Intelligence for Biomedical Applications is ideal for academicians, researchers, students, engineers, and experts from the fields of computer science, biomedical, medical, and health sciences. It also welcomes all readers of different fields to be informed about use cases of XAI in black-box artificial intelligence. In this sense, the book can be used for both teaching and reference source purposes.
DOWNLOAD:
https://rapidgator.net/file/ee837ee7faa166a1fd1719759564e079/978-981-95-3811-9.rar
https://nitroflare.com/view/2265DE4FD9136B8/978-981-95-3811-9.rar
We need your support!
Make a donation to help us stay online
Bitcoin (BTC)
bc1q08g9d22cxkawsjlf8etuek2pc9n2a3hs4cdrld
Bitcoin Cash (BCH)
qqvwexzhvgauxq2apgc4j0ewvcak6hh6lsnzmvtkem
Ethereum (ETH)
0xb55513D2c91A6e3c497621644ec99e206CDaf239
Litecoin (LTC)
ltc1qt6g2trfv9tjs4qj68sqc4uf0ukvc9jpnsyt59u
USDT (ERC20)
0xb55513D2c91A6e3c497621644ec99e206CDaf239
USDT (TRC20)
TYdPNrz7v1P9riWBWZ317oBgJueheGjATm
Information |
|||
 |
Users of GUESTS are not allowed to comment this publication. | ||