{"id":"W4234370987","doi":"10.2196/27990","title":"A Personalized Ontology-Based Decision Support System for Complex Chronic Patients: Retrospective Observational Study","year":2022,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Regional Development Fund","keywords":"Clinical decision support system; SNOMED CT; Medicine; Health informatics; Ontology; Interoperability; Terminology; Polypharmacy; Health care; Decision support system; Informatics; Semantic interoperability; Medical prescription; eHealth; Computer science; Data mining; Intensive care medicine; Nursing; World Wide Web; Public health","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":[0.003487197,0.0003284587,0.0006844068,0.001910451,0.0009517483,0.001132211,0.0005491697,0.0007963345,0.002480872],"category_scores_gemma":[0.0153183,0.0003925577,0.0008395516,0.001855724,0.0004114982,0.001032907,0.0009543552,0.0007980978,0.0004510855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001640053,"about_ca_system_score_gemma":0.002065593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008700578,"about_ca_topic_score_gemma":0.007486822,"domain_scores_codex":[0.9977544,0.0008356611,0.0004660523,0.0004173199,0.000341629,0.0001850735],"domain_scores_gemma":[0.9911459,0.003797079,0.002196576,0.0007992937,0.001292973,0.0007681162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000362203,0.001244466,0.9821764,0.0002439514,0.0001311829,0.001239554,0.002397378,0.0003010898,0.000106502,0.0001633995,0.001274467,0.0103594],"study_design_scores_gemma":[0.0002798358,0.002774615,0.9634662,0.0004576531,0.000480288,0.003706532,0.01258514,0.006940479,0.0003736362,0.0006271238,0.008186478,0.0001221263],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962774,0.0002509832,0.0009173992,0.00009371519,0.000007272453,0.0002931513,0.001642006,0.00001172792,0.000506464],"genre_scores_gemma":[0.9951501,0.0002691524,0.001916531,0.0001039537,0.00001578959,0.0003550153,0.001985871,0.000009117698,0.0001944752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008700578,"threshold_uncertainty_score":0.01844227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3326479509856947,"score_gpt":0.5674309284707426,"score_spread":0.2347829774850479,"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."}}