Review ArticlesArtificial Intelligence in Pathology: A Simple and Practical GuideYao, Keluo MD*; Singh, Amol BS†; Sridhar, Kaushik MS*; Blau, John L. MD‡; Ohgami, Robert S. MD, PhD*Author Information *Department of Pathology, University of California, San Francisco, San Francisco †Department of Computer Science, Stanford University, Stanford, CA ‡Department of Pathology, University of Iowa, Iowa City, IA K.Y., A.S., K.S., and J.L.B. contributed equally. The authors have no funding or conflicts of interest to disclose. All figures can be viewed online in color at www.anatomicpathology.com. Reprints: Keluo Yao, MD, Department of Pathology, University of California, San Francisco, San Francisco, CA 94143 (e-mail: [email protected]). Advances In Anatomic Pathology: November 2020 - Volume 27 - Issue 6 - p 385-393 doi: 10.1097/PAP.0000000000000277 Buy Metrics Abstract Artificial intelligence (AI) is having an increasing impact on the field of pathology, as computation techniques allow computers to perform tasks previously performed by people. Here, we offer a simple and practical guide to AI methods used in pathology, such as digital image analysis, next-generation sequencing, and natural language processing. We not only provide a comprehensive review, but also discuss relevant history and future directions of AI in pathology. We additionally provide a short tabular dictionary of AI terminology which will help practicing pathologists and researchers to understand this field. Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.