Artificial Intelligence in Medicine: Technical Basis and Clinical Applications

by Lei Xing (Editor), Maryellen L. Giger (Editor), James K. Min (Editor)

Artificial Intelligence Technical Basis and Clinical Applications presents a comprehensive overview of the field, ranging from its history and technical foundations, to specific clinical applications and finally to prospects. Artificial Intelligence (AI) is expanding across all domains at a breakneck speed. Medicine, with the availability of large multidimensional datasets, lends itself to strong potential advancement with the appropriate harnessing of AI. The integration of AI can occur throughout the continuum of from basic laboratory discovery to clinical application and healthcare delivery. Integrating AI within medicine has been met with both excitement and scepticism. By understanding how AI works, and developing an appreciation for both limitations and strengths, clinicians can harness its computational power to streamline workflow and improve patient care. It also provides the opportunity to improve upon research methodologies beyond what is currently available using traditional statistical approaches. On the other hand, computers scientists and data analysts can provide solutions, but often lack easy access to clinical insight that may help focus their efforts. This book provides vital background knowledge to help bring these two groups together, and to engage in more streamlined dialogue to yield productive collaborative solutions in the field of medicine.

568 pages, Paperback

Published September 17, 2020

Reviews

[Teresa Thompson]

This book serves as a vital compendium for individuals involved in or contemplating the exploration of AI within the biomedical sphere. Encompassing a broad range of biomedical topics, this book presents a comprehensive understanding of cutting-edge AI methods that are transforming clinical practices.

Featuring a thorough and timely overview of the AI landscape in healthcare by renowned and trustworthy experts, this book furnishes an excellent framework for students and researchers seeking to investigate, devise, and implement medical AI innovations.