Textbook in PDF format

The advent of Generative AI has democratized access to AI, prompting nearly everyone in healthcare organizations - from frontline workers to business leaders – to ask pressing questions: How can I be better equipped to support AI adoption meaningfully? How do I ensure I ask the right questions? What cautions should I exercise as I think about AI/Machine Learning (ML) in my business process? This book aims to answer these and other such questions and to empower healthcare professionals, at all levels, by providing them knowledge across various aspects of AI/ML, enabling them (at least in part) to realize positive, lasting business value from AI and ML initiatives. This book draws upon my experience of working in healthcare AI/ML, lessons I learned while observing leaders in this space trying to make a difference, and research (for evolving topics like sustainable AI development and securing AI/ML systems). This book provides readers with actionable insights to build responsible, secure, and sustainable AI/ML solutions in healthcare and delves into key principles for scaling AI/ML value delivery, including establishing Machine Learning Operations (MLOps) processes and launching citizen Data Science programs. Preface Healthcare AI/ML essentials Leading in the age of AI Begin with the end in mind Navigate healthcare AI/ML responsibly Securing AI/ML systems Path to sustainable AI in healthcare Getting ready to scale Looking ahead APPENDIXS