{"id":"W4415110146","doi":"10.2196/63767","title":"Deep Learning Models to Screen Electronic Health Records for Breast and Colorectal Cancer Progression: Performance Evaluation Study","year":2025,"lang":"en","type":"article","venue":"JMIR AI","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Research Institute in Oncology and Hematology; University of Waterloo; CancerCare Manitoba","funders":"","keywords":"Deep learning; Health records; Chart; Electronic health record; Colorectal cancer; Breast cancer","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006237658,0.001778865,0.001008044,0.001356351,0.0003954811,0.0009725347,0.001237403,0.001424168,0.001344829],"category_scores_gemma":[0.01222963,0.0003781562,0.001034322,0.0009903267,0.0004142285,0.001147045,0.001209818,0.001668813,0.0006255285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00206034,"about_ca_system_score_gemma":0.00249195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03605272,"about_ca_topic_score_gemma":0.02531644,"domain_scores_codex":[0.9976743,0.00105995,0.000241142,0.0004001523,0.0003580588,0.0002662901],"domain_scores_gemma":[0.9922462,0.004411339,0.0005953178,0.0005868711,0.001745552,0.0004147548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004996336,0.004619701,0.210468,0.0006847588,0.001786053,0.0003092604,0.0001857759,0.4308601,0.002446053,0.0008343996,0.01698774,0.3258219],"study_design_scores_gemma":[0.0001388367,0.0009960731,0.01045718,0.00005982731,0.0001794889,0.00009219719,0.00006749886,0.9854295,0.001449706,0.0004501462,0.0006555013,0.00002394118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9689915,0.004294915,0.01743037,0.001573068,0.0002253946,0.0002489571,0.003273267,0.001250314,0.002712208],"genre_scores_gemma":[0.9761773,0.0007761124,0.01394452,0.0002777393,0.00006600157,0.000128552,0.007172669,0.00003335337,0.001423816],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03605272,"threshold_uncertainty_score":0.07168573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02988774123357946,"score_gpt":0.3974202329236167,"score_spread":0.3675324916900372,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}