{"id":"W3133353820","doi":"10.3390/informatics8010012","title":"Visual Analytics for Electronic Health Records: A Review","year":2021,"lang":"en","type":"review","venue":"Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Visual analytics; Analytics; Computer science; Data science; Cultural analytics; Interactive visual analysis; Software analytics; Resource (disambiguation); Visualization; Health care; Semantic analytics; World Wide Web; Artificial intelligence; Software","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.004874245,0.001081694,0.001732742,0.009342019,0.0005456687,0.002639546,0.001985359,0.001554881,0.005687449],"category_scores_gemma":[0.01995173,0.0006319875,0.001993802,0.009993166,0.001120001,0.003340658,0.001491742,0.001647282,0.001479874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001695591,"about_ca_system_score_gemma":0.00507507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005269143,"about_ca_topic_score_gemma":0.006668473,"domain_scores_codex":[0.9971986,0.0008925365,0.0006556769,0.0002729754,0.0008846074,0.00009566761],"domain_scores_gemma":[0.9772977,0.01802816,0.001215373,0.0003563556,0.002867755,0.0002347612],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000059201,0.00005381868,0.00042646,0.1296891,0.0002778727,0.00008505365,0.0002627947,0.000297103,0.0002817835,0.00351084,0.02361919,0.8414369],"study_design_scores_gemma":[0.00003786663,0.0001448668,0.003176995,0.2307017,0.001199816,0.001133548,0.0004492708,0.0003895842,0.0005274172,0.004756457,0.7573909,0.00009152742],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00007868466,0.9986235,0.000283125,0.0003374939,0.00009622028,0.00002144548,0.00003388635,0.00001157804,0.0005140855],"genre_scores_gemma":[0.000839071,0.9979808,0.0007121069,0.0002111546,0.00007555839,0.00002987467,0.00004517842,0.000005021222,0.0001013659],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.009342019,"threshold_uncertainty_score":0.02577776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07350255607996942,"score_gpt":0.4328210915242381,"score_spread":0.3593185354442687,"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."}}