{"id":"W2106981782","doi":"10.1145/2110363.2110408","title":"Unsupervised pattern discovery in electronic health care data using probabilistic clustering models","year":2012,"lang":"en","type":"article","venue":"","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":149,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Pacific Institute for the Mathematical Sciences","keywords":"Cluster analysis; Computer science; Probabilistic logic; Health records; Data mining; Unsupervised learning; Machine learning; Artificial intelligence; Cluster (spacecraft); Statistical model; Process (computing); Health care","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.005574734,0.0006180792,0.00106094,0.002519205,0.0005902998,0.001540675,0.002078384,0.001369064,0.0005986473],"category_scores_gemma":[0.02330127,0.0006613809,0.00128411,0.002309737,0.001126732,0.002192021,0.001142235,0.001381182,0.0002430198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001478296,"about_ca_system_score_gemma":0.001091968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007715324,"about_ca_topic_score_gemma":0.009603219,"domain_scores_codex":[0.9970478,0.001470707,0.0001823245,0.0007078992,0.000434211,0.0001570877],"domain_scores_gemma":[0.978528,0.016807,0.002302984,0.001192608,0.0009718568,0.0001975983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001094839,0.0001094442,0.01350955,0.00007961497,0.0001519849,0.0001349938,0.0003377208,0.9162161,0.0006503555,0.02334777,0.001175593,0.04417751],"study_design_scores_gemma":[0.00000445271,0.000005880403,0.000521898,0.00000400728,0.00000435099,0.00001470668,0.00001028249,0.9903301,0.00007551347,0.00893252,0.00009171903,0.000004659898],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1116375,0.0003472801,0.8854821,0.0008481423,0.00002323815,0.000122404,0.00053468,0.0003735466,0.0006312627],"genre_scores_gemma":[0.7624791,0.0004713069,0.2336578,0.0001754278,0.00007823201,0.0003007207,0.00149438,0.00005824836,0.00128471],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007715324,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07369182579551344,"score_gpt":0.2897209502123568,"score_spread":0.2160291244168434,"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."}}