Refining Clinical Evaluation Metrics

Background: Evaluating foundation models for clinical prediction requires metrics that accurately reflect clinical utility, such as predicting the early onset of a disease rather than merely repeating chronic diagnoses.

Question / Future Work: It is necessary to establish standardized evaluation protocols that explicitly separate the model’s ability to anticipate true disease onsets from its tendency to repeat known historical events. Furthermore, research should focus on developing and standardizing metrics that are directly tied to specific clinical use cases, such as time-to-event variants or onset timing metrics, to complement prevalence-sensitive metrics like AUPRC.