Academic Radiology Departments Should Lead Artificial Intelligence Initiatives

Samantha M Santomartino; Eliot Siegel; Paul H Yi

doi:10.1016/j.acra.2022.07.011

Academic Radiology Departments Should Lead Artificial Intelligence Initiatives

Acad Radiol. 2023 May;30(5):971-974. doi: 10.1016/j.acra.2022.07.011. Epub 2022 Aug 11.

Authors

Samantha M Santomartino¹, Eliot Siegel¹, Paul H Yi²

Affiliations

¹ University of Maryland Medical Intelligent Imaging (UM2ii) Center, Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, W. Baltimore Street, First Floor, Rm. 1172, 21201 Baltimore, MD.
² University of Maryland Medical Intelligent Imaging (UM2ii) Center, Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, W. Baltimore Street, First Floor, Rm. 1172, 21201 Baltimore, MD; Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD. Electronic address: pyi@som.umaryland.edu.

PMID: 35965155
DOI: 10.1016/j.acra.2022.07.011

Abstract

Rationale and objectives: With a track record of innovation and unique access to digital data, radiologists are distinctly positioned to usher in a new medical era of artificial intelligence (AI).

Materials and methods: In this Perspective piece, we summarize AI initiatives that academic radiology departments should consider related to the traditional pillars of education, research, and clinical excellence, while also introducing a new opportunity for engagement with industry.

Results: We provide early successful examples of each as well as suggestions to guide departments towards future success.

Conclusion: Our goal is to assist academic radiology leaders in bringing their departments into the AI era and realizing its full potential in our field.

Keywords: Artificial intelligence; radiology educational initiatives perspective.

MeSH terms

Artificial Intelligence
Forecasting
Humans
Radiologists
Radiology Department, Hospital*
Radiology* / education