Название: Explainable and Responsible Artificial Intelligence in Healthcare
Автор: Rishabha Malviya, Sonali Sundram
Издательство: Wiley-Scrivener
Год: 2025
Страниц: 377
Язык: английский
Формат: pdf (true), epub
Размер: 20.1 MB

This book presents the fundamentals of Explainable Artificial Intelligence (XAI) and Responsible Artificial Intelligence (RAI), discussing their potential to enhance diagnosis, treatment, and patient outcomes.

This book explores the transformative potential of Explainable Artificial Intelligence (XAI) and Responsible AI (RAI) in healthcare. It provides a roadmap for navigating the complexities of healthcare-based AI while prioritizing patient safety and well-being. The content is structured to highlight topics on smart health systems, neuroscience, diagnostic imaging, and telehealth. The book emphasizes personalized treatment and improved patient outcomes in various medical fields. In addition, this book discusses osteoporosis risk, neurological treatment, and bone metastases. Each chapter provides a distinct viewpoint on how XAI and RAI approaches can help healthcare practitioners increase diagnosis accuracy, optimize treatment plans, and improve patient outcomes.

The goal of the Computer Science and AI field of NLP is to automatically analyze, represent, and interpret human language. In recent years, NLP has become a vibrant field of study, receiving substantial interest from a range of research communities. Natural language processing (NLP) is essential to smart healthcare because it allows robots to comprehend and communicate with humans through the use of human language, which is the fundamental mode of communication for intelligent systems. Text and speech are the two main ways that human language is expressed. Text records, articles, dialogues, and more may all be examples of this.

Readers will find the book:
explains recent XAI and RAI breakthroughs in the healthcare system;
discusses essential architecture with computational advances ranging from medical imaging to disease diagnosis;
covers the latest developments and applications of XAI and RAI-based disease management applications;
demonstrates how XAI and RAI can be utilized in healthcare and what problems the technology faces in the future.

Audience:
The main audience for this book is targeted to scientists, healthcare professionals, biomedical industries, hospital management, engineers, and IT professionals interested in using AI to improve human health.