Introduction to Artificial Intelligence (AI) and Machine Learning (ML) in Pathology & Medicine: Generative & Non-Generative AI Basics
生成语法
人工智能
病理
计算机科学
医学
作者
Hooman H. Rashidi,Joshua Pantanowitz,Matthew G Hanna,Ahmad P. Tafti,Parth Sanghani,Adam Buchinsky,Brandon D. Fennell,Mustafa Deebajah,Sarah Wheeler,Thomas M. Pearce,Ibrahim Abukhiran,Scott Robertson,Octavia M. Peck Palmer,Michal Gur,Nam K. Tran,Liron Pantanowitz
This manuscript serves as an introduction to a comprehensive 7-part review article series on artificial intelligence (AI) and machine learning (ML) and their current and future influence within pathology and medicine. This introductory review provides a comprehensive grasp of this fast-expanding realm and its potential to transform medical diagnosis, workflow, research, and education. Fundamental terminology employed in AI-ML is covered using an extensive dictionary. The article also provides a broad overview of the main domains in the AI-ML field, encompassing both generative and nongenerative (traditional) AI, thereby serving as a primer to the other 6 review articles in this series that describe the details about statistics, regulations, bias, ethical dilemmas, and ML-Ops in AI-ML. The intent of these review articles is to better equip individuals who are or will be working in an AI-enabled health care system.