Fields
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Field
Machine learning for medicine and health
Medical ML covers image analysis (classification, segmentation, foundation models for radiology, pathology, ophthalmology), prediction from electronic health records and ICU time series, evaluation of language models on medical question answering and clinical tasks, and physiological signal analysis (ECG, EEG, sleep). Results are reported with discrimination and calibration metrics on patient-level splits, ideally with external validation on another site; most clinically relevant datasets require data-use agreements, and leakage across patients or sites is the main validity threat.