{"id":"W2979743968","doi":"10.1109/embc.2019.8856985","title":"Prediction of Patient-specific Acute Hypotensive Episodes in ICU Using Deep Models","year":2019,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Logistic regression; Task (project management); Baseline (sea); Computer science; Cohort; Deep learning; Artificial intelligence; Medicine; Regression; Machine learning; Emergency medicine; Internal medicine; Statistics; Mathematics","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":[0.0008505195,0.0008515039,0.0006300248,0.0006489077,0.0001718053,0.0006254448,0.0005780942,0.0008072435,0.0008175222],"category_scores_gemma":[0.003285774,0.0003169451,0.0005324528,0.0004262804,0.0001661162,0.0005299554,0.0006528004,0.001441924,0.0003071258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005474164,"about_ca_system_score_gemma":0.0007120412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008795719,"about_ca_topic_score_gemma":0.009573843,"domain_scores_codex":[0.9997388,0.00006830328,0.00002744668,0.00007013776,0.00003274456,0.0000626151],"domain_scores_gemma":[0.9988289,0.0006674406,0.0001497779,0.00006095321,0.0001601001,0.0001326702],"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":[0.0008697036,0.0007768268,0.1754113,0.00009181123,0.0002633311,0.0008317134,0.0001152766,0.6924264,0.002615617,0.0006837575,0.006783469,0.1191307],"study_design_scores_gemma":[0.000007201101,0.00004004419,0.003714698,0.00000583755,0.000008321794,0.000021629,0.00001146551,0.9954059,0.0002868235,0.0004231888,0.00007074927,0.000004182745],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.913911,0.0008909204,0.07996204,0.0013577,0.0001377572,0.00006162636,0.001877303,0.0006677071,0.001134069],"genre_scores_gemma":[0.9921378,0.0001484371,0.00575242,0.0001107358,0.00004124163,0.00003078368,0.001250132,0.00001054257,0.0005178454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008795719,"threshold_uncertainty_score":0.01748902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03399633038464408,"score_gpt":0.2556286890267401,"score_spread":0.221632358642096,"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."}}