Cautious optimism on foundation models in medical imaging balancing privacy and innovation

Abstract

Foundation models for medical imaging offer transformative healthcare potential but risk patient re-identification through latent demographic and identity signals retained during training. A recent study in npj Digital Medicine reports re-identification rates up to 94 percent in retinal imaging using FMs, yet does not disentangle causality or propose mitigation strategies. Urgent technical safeguards and policy frameworks are needed to balance innovation with individual privacy and protect confidentiality.

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