A Basic Primer of Artificial Intelligence for Radiologists. (1st January 2022)

• Record Type: Journal Article
• Authors: Stahl, Ethan; Blumer, Steven L.
• Is Part Of: Contemporary diagnostic radiology. Volume 45:Number 1(2022)
• Publication Date: 2022-01-01
• Subjects: Artificial Intelligence -- Machine Learning -- Neural Networks -- Natural Language Processing; Medical radiology -- Periodicals; Diagnosis, Radioscopic -- Periodicals; Diagnosis -- Periodicals; Radiology -- Periodicals; Diagnosis, Radioscopic; Medical radiology; Periodicals; 616.0757
• DOI: 10.1097/01.CDR.0000804996.57509.75
• Languages: English
• ISSNs: 0149-9009

Abstract

Abstract : Artificial intelligence (AI) comprises computer systems that behave in ways previously thought to require human intelligence.1 AI and related technologies are increasingly prevalent in business and society and are beginning to be applied to health care.2 Within health care, AI has increasingly influenced the field of radiology, and its role is likely only to grow in the future. Within radiology, AI has demonstrated benefits in the areas of image analysis and interpretation, various noninterpretive domains, and resident training. And yet, AI remains vaguely and incompletely understood by a great many practicing radiologists, radiology residents, and students considering a career in radiology. The purpose of this article is to describe the primary current and potential future applications of AI to the field of radiology and to define some of the key terms used in discussions of AI. This article is meant to provide readers with a clear, foundational understanding of AI in radiology and to equip radiologists with literacy and fluency in the AI lexicon.