Explainable AI in Health Informatics / edited by Rajanikanth Aluvalu, Mayuri Mehta, Patrick Siarry.

Format:

Book

Author/Creator:

Aluvalu, Rajanikanth.

Contributor:

Mehta, Mayuri.

Siarry, Patrick.

Series:

Computational Intelligence Methods and Applications, 2510-1773

Language:

English

Subjects (All):

Artificial intelligence.

Medical informatics.

Biomedical engineering.

Artificial Intelligence.

Health Informatics.

Medical and Health Technologies.

Local Subjects:

Artificial Intelligence.

Health Informatics.

Medical and Health Technologies.

Physical Description:

1 online resource (287 pages)

Edition:

1st ed. 2024.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2024.

Summary:

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.

Contents:

Chapter 1. Introduction to Explainable AI

Chapter 2. Explainable AI Methods and Applications

Chapter 3. Unveil the Black Box Model for Healthcare Explainable AI

Chapter 4. Explainable AI: Methods, Frameworks, and Tools for Healthcare 5.0

Chapter 5. Explainable AI in Disease Diagnosis

Chapter 6. Explainable Artificial Intelligence in Drug Discovery

Chapter 7. Explainable AI for Big Data Control

Chapter 8. Patient Data Analytics using XAI- Existing Tools & Case Studies

Chapter 9. Enhancing Diagnosis of Kidney Ailments from CT Scan with Explainable AI

Chapter 10. Explainable AI for Colorectal Cancer Classification

Chapter 11. Explainable AI (XAI)-based Robot-Assisted Surgical classification Procedure

Chapter 12. Explainable AI Case Studies in Healthcare.

Notes:

Description based on publisher supplied metadata and other sources.

Other Format:

Print version: Aluvalu, Rajanikanth Explainable AI in Health Informatics

ISBN:

9789819737055

OCLC:

1445769490