AI in Radiology: Bridging the Gap Between Technology and Patient Care

Authors

Jordan Watts, Marshall University
Jeffrey Larson, Marshall UniversityFollow
Kasi Gorli, Marshall University
Alberto Coustasse, Marshall UniversityFollow

Document Type

Conference Proceeding

Publication Date

3-27-2025

Abstract

Artificial Intelligence (AI) integration in healthcare, particularly within radiology, has grown rapidly, with 400 out of 520 FDA-approved AI algorithms explicitly designed for radiological applications as of 2023. AI has shown significant potential for enhancing healthcare delivery and improving patient outcomes (AHA, 2023); however, understanding the barriers, facilitators, and implications of AI implementation in radiology remains fragmented across existing studies. This study investigates AI's impact on radiology in three critical areas: diagnostic accuracy, interpretation times, and clinical workflow efficiency. We synthesize key findings regarding AI's contributions to radiology practices through a comprehensive literature review of 29 articles published between 2015 and 2024, sourced from databases including PubMed, EBSCOhost, and Google Scholar.

Comments

Copyright © 2025 The Authors.

Recommended Citation

Watts J., Larson J., Gorli K., and Coustasse A. (2025, March 27-28). AI in radiology: Bridging the gap between technology and patient care. Appalachian Research in Business Symposium March 27-28, 2025. Marshall University, Huntington, WV.