Related Experiment Video
Updated: Nov 17, 2025

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
Published on: July 11, 2025
Training opportunities of artificial intelligence (AI) in radiology: a systematic review
Floor Schuur1, Mohammad H Rezazade Mehrizi2, Erik Ranschaert3,4
1Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Objectives:
The aim is to offer an overview of the existing training programs and critically examine them and suggest avenues for further development of AI training programs for radiologists.
Methods:
Deductive thematic analysis of 100 training programs offered in 2019 and 2020 (until June 30). We analyze the public data about the training programs based on their "contents," "target audience," "instructors and offering agents," and "legitimization strategies."
Results:
There are many AI training programs offered to radiologists, yet most of them (80%) are short, stand-alone sessions, which are not part of a longer-term learning trajectory. The training programs mainly (around 85%) focus on the basic concepts of AI and are offered in passive mode. Professional institutions and commercial companies are active in offering the programs (91%), though academic institutes are limitedly involved.
Conclusions:
There is a need to further develop systematic training programs that are pedagogically integrated into radiology curriculum. Future training programs need to further focus on learning how to work with AI at work and be further specialized and customized to the contexts of radiology work.
Key Points:
• Most of AI training programs are short, stand-alone sessions, which focus on the basics of AI. • The content of training programs focuses on medical and technical topics; managerial, legal, and ethical topics are marginally addressed. • Professional institutions and commercial companies are active in offering AI training; academic institutes are limitedly involved.
More Related Videos
05:49Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
Published on: February 23, 2024
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018
Related Concept Videos
Radiological Investigation I: X-ray and CT
Issues And Trends In Healthcare Delivery System
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...