Artificial Intelligence: Applications in Healthcare Delivery

Description

Artificial Intelligence in Healthcare, Seen Through the Lens of Real Delivery

Artificial Intelligence: Applications in Healthcare Delivery is a substantial edited collection focused on a question that matters far more than technical novelty alone: how do AI methods actually fit into the daily realities of healthcare? The book’s chapters move across clinical and operational settings, showing AI as something that must work inside complex systems of people, workflows, and decision-making—not just in a lab or on a whiteboard.

Edited by Sandeep Reddy and published by Routledge, this volume gathers work on topics such as chronic disease screening, drug discovery, mammographic screening, clinical data science, perioperative safety, sepsis detection, clinical trials, neuromorphic chips, thyroidology, and artificial empathy. The range is wide, but the unifying theme is practical application: how AI supports diagnosis, prediction, administration, and care delivery in real healthcare environments.

Why This Book Stands Out

The foreword frames the book around implementation science and the challenge of embedding AI into healthcare settings effectively. That makes this title especially useful for readers who want more than a general introduction to machine learning jargon. It is interested in the harder question: what happens when AI meets clinical practice, institutional constraints, and real-world variation?

• Edited volume format with multiple specialist chapters
• Healthcare-first perspective on AI use cases
• Strong emphasis on implementation and application
• Broad coverage across clinical, administrative, and research contexts

Who Will Find It Useful?

This ebook is well suited to healthcare professionals, clinical managers, researchers, informaticians, and technology-focused readers who want a grounded view of AI in medicine. It is especially relevant for anyone exploring how AI tools move from promising models to workable healthcare practice.

If you are building a digital health collection, this is a title that belongs alongside serious books on medical AI, implementation science, and health informatics.