Design a machine learning model to assist in diagnosing diseases from medical imaging data.
Instruction: Discuss your approach to data collection, preprocessing, model selection, training, and validation, including how you would handle the ethical considerations involved. Fictional research-only brief: a model prioritizes an imaging review queue; it does not issue diagnoses. Data come from three sites, with repeated studies per patient. One site uses a scanner absent from training. All studies must still receive the normal clinician review within the existing deadline. Define a baseline, split, failure behavior and evidence needed before a clinical pilot.
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I would treat this as a clinical decision-support system, not an autonomous diagnosis system. That distinction matters because the design has to optimize for clinician trust, calibration, and safe workflow integration, not just benchmark accuracy.
Data quality and...