Review ArticlesA Practical Guide to Artificial Intelligence–Based Image Analysis in RadiologyWeikert, Thomas MD; Cyriac, Joshy MSc; Yang, Shan PhD; Nesic, Ivan MSc; Parmar, Victor MSc; Stieltjes, Bram MD, PhDAuthor Information From the Department of Radiology, University Hospital Basel, Basel, Switzerland. Received for publication May 21, 2019; and accepted for publication, after revision, June 22, 2019. Conflicts of interest and sources of funding: none declared. Correspondence to: Thomas Weikert, MD, Department of Radiology, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland. E-mail: email@example.com. Online date: September 10, 2019 Investigative Radiology: January 2020 - Volume 55 - Issue 1 - p 1-7 doi: 10.1097/RLI.0000000000000600 Buy Metrics Abstract The use of artificial intelligence (AI) is a powerful tool for image analysis that is increasingly being evaluated by radiology professionals. However, due to the fact that these methods have been developed for the analysis of nonmedical image data and data structure in radiology departments is not “AI ready”, implementing AI in radiology is not straightforward. The purpose of this review is to guide the reader through the pipeline of an AI project for automated image analysis in radiology and thereby encourage its implementation in radiology departments. At the same time, this review aims to enable readers to critically appraise articles on AI-based software in radiology. Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.