Discover the essential insights and practical applications of explainable AI in healthcare that will empower professionals and enhance patient trust with Explainable AI in the Healthcare Industry, a must-have resource.

Explainable AI (XAI) has significant implications for the healthcare industry, where trust, accountability, and interpretability are crucial factors for the adoption of artificial intelligence. XAI techniques in healthcare aim to provide clear and understandable explanations for AI-driven decisions, helping healthcare professionals, patients, and regulatory bodies to better comprehend and trust the AI models' outputs.

Explainable AI in the Healthcare Industry presents a comprehensive exploration of the critical role of explainable AI in revolutionizing the healthcare industry. With the rapid integration of AI-driven solutions in medical practice, understanding how these models arrive at their decisions is of paramount importance. The book delves into the principles, methodologies, and practical applications of XAI techniques specifically tailored for healthcare settings.

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Yes, you can access Explainable Artificial Intelligence in the Healthcare Industry by Abhishek Kumar,T. Ananth Kumar,Prasenjit Das,Chetan Sharma,Ashutosh Kumar Dubey in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Year

Print ISBN

eBook ISBN

Edition

Topic

Computer Science

Subtopic

Artificial Intelligence (AI) & Semantics

Index

Computer Science

Preface
Cover
Series Page
Title Page
Copyright Page
Contents
Preface
Chapter 1 A Review on Explainable Artificial Intelligence for Healthcare
Chapter 2 Explainable Artificial Intelligence (XAI) in Healthcare: Fostering Transparency, Accountability, and Responsible AI Deployment
Chapter 3 Illuminating the Diagnostic Path: Unveiling Explainability in Medical Imaging
Chapter 4 HealsHealthAI: Unveiling Personalized Healthcare Insights with Open Source Fine-Tuned LLM
Chapter 5 Introduction to Explainable AI in EEG Signal Processing: A Review
Chapter 6 Transparency in Disease Diagnosis: Leveraging Interpretable Machine Learning in Healthcare
Chapter 7 Transparency in Text: Unraveling Explainability in Healthcare Natural Language Processing
Chapter 8 Introduction to Explainable AI in Healthcare: Enhancing Transparency and Trust
Chapter 9 Interpretable Machine Learning Techniques
Chapter 10 Interpretable Machine Learning Techniques in AI
Chapter 11 Interpretable Machine Learning Techniques in Medical System—The Role of Data Analytics and Machine Learning
Chapter 12 Interpretable AI: Shedding Light on Medical Image Analysis Using Machine Learning Techniques
Chapter 13 Exploring the Role of Explainable AI in Women’s Health: Challenges and Solutions
Chapter 14 Explainable AI in Healthcare: Introduction
Chapter 15 Ethical Implications of Emotion Recognition Technology in Mental Healthcare: Navigating Privacy, Bias, and Therapeutic Boundaries
Chapter 16 Bridging the Gap: Clinical Adoption and User Perspectives of Explainable AI in Healthcare
Chapter 17 Application of AI-Based Technologies in the Healthcare Sector: Opportunities, Challenges, and Its Impact—Review
Chapter 18 A Complete Road Map for Interpretable Machine Learning Techniques Harnessing Various Real-Time Applications
Chapter 19 Future Research Directions: Explainable Artificial Intelligence in Healthcare Industry
Chapter 20 Real-World Applications of Explainable AI in Healthcare
Chapter 21 Explainable AI in Medical Imaging, Personalized Medicine, and Bias Reduction: A New Era in Healthcare
Chapter 22 Understanding Explainability in Medical Imaging
Chapter 23 Explainability and Regulatory Compliance in Healthcare: Bridging the Gap for Ethical XAI Implementation
Chapter 24 Envisioning Explainable AI: Significance, Real-Time Applications, and Challenges in Healthcare
Chapter 25 Enlightened XAI: Illuminating Ethics and Equitable Explainability
Chapter 26 Enhancing Trust and Collaboration Using Explainability in Natural Language Processing for AI-Driven Healthcare
About the Editors
Index
Also of Interest
EULA

About this book

Frequently asked questions

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Table of contents