{"id":"W3013366438","doi":"10.2196/16008","title":"Prediction of Medical Concepts in Electronic Health Records: Similar Patient Analysis","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Foundation","keywords":"Health records; Medical record; Electronic health record; Computer science; Data science; Medicine; Medical emergency; Health care; Radiology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001444141,0.0001479238,0.0005107725,0.0002417487,0.00005082582,0.00002655552,0.001103384,0.0002498799,0.0003269613],"category_scores_gemma":[0.001011573,0.0001288671,0.0001144419,0.001982135,0.00008712291,0.000323408,0.0003566281,0.001133061,0.00001863494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001615037,"about_ca_system_score_gemma":0.001540852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002028872,"about_ca_topic_score_gemma":0.0001287565,"domain_scores_codex":[0.9948635,0.0002927954,0.001540794,0.0001894108,0.002611556,0.0005019214],"domain_scores_gemma":[0.9979968,0.0002460562,0.0004787988,0.0003830983,0.00008579114,0.0008094371],"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":[0.00005445419,0.0004448093,0.08942884,0.002239309,0.000358114,0.00004964786,0.1496986,0.003613124,7.67924e-7,0.02306727,0.02537313,0.7056719],"study_design_scores_gemma":[0.0004567069,0.0006894509,0.003256828,0.0001208595,0.000007949629,0.000006786262,0.0006153928,0.9810752,0.000004604048,0.00009804188,0.0135746,0.00009356727],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2470931,0.000650704,0.6253537,0.1234435,0.0005039269,0.001198442,0.00003202452,0.0005221796,0.001202386],"genre_scores_gemma":[0.9772846,0.0003637121,0.005673061,0.01649404,0.00008575607,0.0000401688,0.000046664,0.000008199993,0.000003811743],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9774621,"threshold_uncertainty_score":0.5255049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02367315814278365,"score_gpt":0.3382679664084237,"score_spread":0.31459480826564,"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."}}