This book provides an overview of the role of AI in medicine and, more generally, of issues at the intersection of mathematics, informatics, and medicine. Its goal is to provide clear, objective, and reasonable information on the issues covered, avoiding any fantasies that the topic “AI” might evoke.

Introduction.- Artificial Intelligence and Tomorrow's Health.- Databases.- Matching an Epidemiological Cohort to Medico-Administrative Databases.- Medical and Administrative Data from Health Insurance.- How the SNIIRAM–PMSI Database Enables the Study of Surgical Practices.- Hospital Databases.- The Experience of the Institut Curie.

This book provides an overview of the role of AI in medicine and, more generally, of issues at the intersection of mathematics, informatics, and medicine. It is intended for AI experts, offering them a valuable retrospective and a global vision for the future, as well as for non-experts who are curious about this timely and important subject. Its goal is to provide clear, objective, and reasonable information on the issues covered, avoiding any fantasies that the topic “AI” might evoke. In addition, the book seeks to provide a broad kaleidoscopic perspective, rather than deep technical details.

 

Presents a vision of the future of medicine enabled by AI Demonstrates the revolution in health care practices now becoming possible thanks to AI Edited by well-known experts including the fields medalist Cedric Villani, who is the current first vice-president of the Scientific Parliamentary Office Explores a number of challenges: technical and technological challenge due to the size of the data involved; ethical and legal challenges like protecting personal data; and challenge of confidence, to convince the actors to overcome their reluctance and share data Includes contributions by leading mathematicians, computer scientists, statisticians, oncologists, surgeons, onco-geneticists, sociologists, hospital administrators, and lawyers to provide the reader with clear, objective, and reasonable information, while avoiding fantasies Highlights various areas of innovation, such as renewing and improving the interpretation of images, modeling tumor growth, predicting response to administered treatments, increasing performance in radiology, pathology and dermatology, taking advantage of genetic data to understand diseases, developing precision medicine, and structuring large databases with vast amounts of data

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