AI and Machine Learning Unpacked: A Practical Guide for Decision Makers in Life Sciences and Healthcare (Paperback) (ISBN-13: 9798999705105)

AI evolves at extraordinary speed, but its foundation remains constant-the core methods explored in this book form the enduring framework upon which AI systems are built.

If you've ever wanted to understand how AI is truly implemented in life sciences and healthcare-without getting lost in formulas-this book is your guide. Written by Corina J. Shtir, PhD, a statistician and former Head & VP of Precision Medicine at Thermo Fisher Scientific, AI and Machine Learning Unpacked demystifies complex algorithms through a strategic and practical lens. It bridges the gap between data science and decision-making, equipping executives, clinicians, and policymakers to engage meaningfully with the technologies transforming their fields. AI is revolutionizing healthcare-but often in ways obscured by jargon, oversimplified headlines, or opaque technical detail. This book cuts through that noise. With precision and clarity, Dr. Shtir explains how data becomes action, how models must be interpreted responsibly, and what leadership must understand to evaluate AI solutions effectively.

Inside, you'll discover:

• Clear distinctions between AI, Machine Learning, Deep Learning, and AI Agents.
• Illustrative analogies that make even abstract machine learning concepts intuitive and relatable.
• Real-world examples and visual takeaways
• Key metrics and evaluation strategies that translate model performance into trustworthy decisions

"A well-crafted and timely resource that bridges the gap between the technical complexity of AI/ML and the strategic needs of healthcare and life sciences leaders. Corina brings clarity, practicality, and relevance, offering a formula-free yet rigorous exploration of machine learning's transformative potential. Her personal journey-from academic to executive leadership-adds authenticity and a powerful call to action for ethical, intentional innovation in our field." - Mark Stevenson, Senior Partner, Flagship Pioneering; Former Executive Vice President and COO, Thermo Fisher Scientific

"Corina has encapsulated in one slender book the practical essence of machine learning as reduced to practice in health care broadly... with real-world examples of their use and value in healthcare and life sciences. This book will enable business leaders to work with their IT and bioinformatics teams or vendors to choose and implement the right ML tool or tools to meet their needs." - Timothy J. Triche, MD, PhD, Professor, Pathology & Pediatrics, Keck School of Medicine at USC, Director, Center for Personalized Medicine, CHLA

"For today's Life Sciences executives, understanding AI/ML is no longer optional-it's essential. Dr. Corina Shtir has given me the tools and confidence to engage meaningfully with our scientists and IT teams, elevating the quality and depth of our conversations. An invaluable resource!" - Rob Brainin, JD, CEO, Champions Oncology; Former Executive VP and CBO at Veracyte

"An essential tool for the non-expert executive, providing a practical guide and gateway into a rapidly emerging field that will become required knowledge for all business leaders in the future." - Peter Silvester, Founder of Q7 Yacht Designs; Former President, Life Sciences Solutions, Thermo Fisher Scientific

"Dr. Shtir masterfully explains the technical foundations of AI and ML without any complex equations and shows how these powerful tools can unlock and expand human creativity to improve our everyday lives." - Hakan Sakul, PhD, President, Precision Dx Strategies; Former VP and Head of Diagnostics, Pfizer

"A clear and straightforward practical survey of the often-cryptic world of Artificial Intelligence... accessible to the lay person yet highly useful to the practitioner." - Scott Taylor, MS, PhD, CEO, Diapeutic; COO, Histologics

Author: Corina J. Shtir
ISBN-13: 9798999705105
Publisher: Dexwell Press
Language: English
Published: 11/06/2025
Pages: 344
Format: Paperback
Weight: 1.30lbs
Size: 9.25h x 7.50w x 0.72d