{"id":"W4415122422","doi":"10.2196/preprints.63767","title":"Deep Learning Models to Screen Electronic Health Records for Breast and Colorectal Cancer Progression: Performance Evaluation Study (Preprint)","year":2024,"lang":"en","type":"article","venue":"","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Colorectal cancer; Breast cancer; Chart; Brier score; Cancer; Deep learning; Stage (stratigraphy)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007464489,0.001838649,0.001091253,0.001277796,0.000382174,0.001280504,0.001264837,0.001433382,0.002169309],"category_scores_gemma":[0.01368343,0.0004238775,0.001264574,0.001008126,0.0003807026,0.001273767,0.001165685,0.00188658,0.001188725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002093777,"about_ca_system_score_gemma":0.002351851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04722779,"about_ca_topic_score_gemma":0.03223374,"domain_scores_codex":[0.9977055,0.00104834,0.0002584664,0.0004254897,0.0003362872,0.0002259761],"domain_scores_gemma":[0.991916,0.004522086,0.0004780765,0.0006553716,0.002013924,0.0004145441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006388069,0.004723563,0.1550648,0.0009128587,0.002242784,0.0002930032,0.0002219163,0.3761425,0.002471731,0.0008715261,0.04091664,0.4097506],"study_design_scores_gemma":[0.0002261654,0.001261324,0.01398903,0.00009672709,0.0002648562,0.00008269838,0.0001099539,0.9799805,0.002101519,0.0005213496,0.001326534,0.00003925647],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9499761,0.0061701,0.0233466,0.002676697,0.0005791164,0.0003854584,0.008646375,0.003287158,0.004932337],"genre_scores_gemma":[0.9494255,0.001343925,0.0225471,0.0005463607,0.0001339642,0.0002593171,0.02197706,0.0001041606,0.003662679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04722779,"threshold_uncertainty_score":0.09390581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0399535450827147,"score_gpt":0.3605331647896667,"score_spread":0.320579619706952,"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."}}