Vol. 24 No. 1
Letter to editor

Reflections on Bias in AI-Based Medical Education

Chiara Rabbito
Società Italiana di Telemedicina, Roma
Carlo Maria Petrini
Istituto Superiore di Sanità, Roma
Antonio Vittorino Gaddi
Società Italiana di Telemedicina, Roma
Pierangelo Veltri
Dipartimento di Ingegneria Informatica, Modellistica, Elettronica e Sistemistica, Università della Calabria, Cosenza
Mario Ettore Giardini
School of Science and Engineering, University of Dundee, UK

Published 2025-05-16

Abstract

Introduction: The advent of Large Language Models in 2022 is requiring a reconsideration of the contents to be included in Artificial Intelligence (AI) training for healthcare personnel.
Objectives: A review of the literature published since the launch of ChatGPT has been performed, to identify which contents are suggested for inclusion in AI training for healthcare personnel.
Methods: the review has been conducted according to the PRISMA-ScR extension to the PRISMA statement. Only items containing primary data have been included, thus excluding literature reviews.
Results: 10101 items have been identified, of which 21 have been selected for review. These include original articles, letters, commentaries, opinion papers, editorials, interviews.
Discussion: The items extracted from the literature address almost exclusively medical training. The analysis failed to identify methodologically robust studies on the contents to be included in AI training for healthcare personnel. There is however consensus on the fact that content on the broader technical, application, ethics, and regulatory aspects should take priority over direct operativity on informatics tools.