INFORMATICS AND AI FOR HEALTHCARE is a comprehensive guide to the rapidly evolving world where health data, information systems, and artificial intelligence converge. Drawing on years of teaching, research, and real-world implementation, the book demystifies how data flows through modern healthcare ecosystems — from molecular and imaging data to electronic health records — and how AI and machine learning transform this data into actionable clinical insights. Written for students, clinicians, engineers, policymakers, and digital health practitioners, this book provides a unified and intuitive introduction to health informatics, data governance, medical imaging AI, NLP, and the foundations of machine learning and transformer-based language models. It bridges the gap between healthcare and computing by offering clear explanations, visual illustrations, and practical examples drawn from real clinical and research settings. In a landscape where fragmented data systems, inconsistent standards, and slow digital adoption continue to challenge health systems, this book outlines the problems and presents pathways toward interoperability, secure data exchange, advanced decision support, and AI-driven diagnostics. Through its structured progression — from fundamental concepts to advanced applications — the book equips readers with the knowledge needed to design, evaluate, and deploy informatics and AI solutions responsibly and effectively.

Foreword / Preface / List of Abbreviations / List of Figures / Introduction to Informatics & AI for Healthcare / Big Data in Healthcare and the present GAPS in Healthcare practices from a Digital Perspective / Healthcare Data and Data Governance / Health IT Systems & Health Information Exchange / Evaluating Health Informatics Technologies and the Associated Challenges / Healthcare Terminology & Syntax: An Informatics Perspective / Healthcare Terminology & Semantics / Health Informatics and Artificial Intelligence: Transforming Medical Imaging with a Focus on MRI / Short Primer in Machine Learning / From Natural Language Processing to Language Modelling / Neural Language Models: From RNNs toward Transformers / The Transformer Architecture and Advances Toward Large-scale AI / AI/ML in Public Health and Health Policy / References / Index.

Postgraduate Students, Professionals & Teachers