Bias, representation, and clinical fidelity in AI-generated images for medical education: a systematic literature review (opens in new tab)

Generative AI text-to-image systems are increasingly used in medical education due to their speed and apparent visual realism, yet they introduce distinct safety and equity risks. Although empirical evaluations are accumulating, evidence on representational bias and clinical fidelity remains fragmented. We conducted a PRISMA-guided systematic review to synthesize findings from 36 empirical studies evaluating AI-generated images in medical teaching, assessment, and patient education contexts. ...