Clinical model evaluation
Begin with the decision a model is intended to inform. Discuss evaluation questions around discrimination, calibration, subgroup performance and the ways a prediction can fail.
Robustness research
Explore what happens when inputs, populations or acquisition conditions change. Define the failure modes that matter before selecting the metrics.
Imaging & radiomics
Investigate quantitative imaging, feature stability and uncertainty. Connect computational questions to the clinical context in which a result would be used.
Research collaboration
Bring a clinical question, a methodological challenge or an evidence gap. Start by discussing the question, available information and what a useful answer would need to show.
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Share the question you are working on and the context behind it.