{"id":"W4402443124","doi":"10.2196/56343","title":"Application of Spatial Analysis on Electronic Health Records to Characterize Patient Phenotypes: Systematic Review","year":2024,"lang":"en","type":"review","venue":"JMIR Medical Informatics","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. National Library of Medicine; National Cancer Institute","keywords":"Geocoding; Medicine; MEDLINE; Medical diagnosis; Data science; Clinical decision support system; Data mining; Computer science; Cartography; Decision support system; Pathology; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0160728,0.001313413,0.004885842,0.01629226,0.000700055,0.003067819,0.002250603,0.001352719,0.003362022],"category_scores_gemma":[0.1020574,0.0009031838,0.008000439,0.0223328,0.001139062,0.003264078,0.001948963,0.001028918,0.0003134377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003268443,"about_ca_system_score_gemma":0.01473531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01379909,"about_ca_topic_score_gemma":0.03484936,"domain_scores_codex":[0.9783638,0.008264991,0.007764603,0.001704037,0.00359419,0.0003083981],"domain_scores_gemma":[0.8740769,0.1012897,0.01453923,0.002562249,0.007187745,0.0003441141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.00011481,0.00001655588,0.005408172,0.9044753,0.01495256,0.0001058165,0.0004134855,0.0003650778,0.00008590456,0.0005906993,0.00245495,0.07101665],"study_design_scores_gemma":[0.0001365218,0.0001124558,0.01181628,0.8994088,0.06554278,0.0003107559,0.000710876,0.0003608942,0.0001878876,0.0007684408,0.02058504,0.00005925506],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002498573,0.9928303,0.001184144,0.0006227782,0.0001501338,0.0004810376,0.00164916,0.00002259671,0.0005612538],"genre_scores_gemma":[0.03999747,0.9535144,0.003887463,0.0006119114,0.0001152584,0.000862228,0.0008943545,0.0000146559,0.0001021431],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01629226,"threshold_uncertainty_score":0.08500218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01914301187259774,"score_gpt":0.3596782694396949,"score_spread":0.3405352575670972,"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."}}