{"id":"W1919353527","doi":"10.1016/j.ejim.2015.06.002","title":"Predicting prolonged length of hospital stay in older emergency department users: Use of a novel analysis method, the Artificial Neural Network","year":2015,"lang":"en","type":"article","venue":"European Journal of Internal Medicine","topic":"Frailty in Older Adults","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"Jewish General Hospital; McGill University","funders":"","keywords":"Medicine; Emergency department; Receiver operating characteristic; Polypharmacy; Emergency medicine; Prospective cohort study; Multilayer perceptron; Positive predicative value; Predictive value; Likelihood ratios in diagnostic testing; Predictive value of tests; Artificial neural network; Machine learning; Internal medicine; Psychiatry","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":[0.001078488,0.0005778416,0.000716029,0.001174792,0.00019522,0.0008994584,0.0004162301,0.0005652805,0.0006122721],"category_scores_gemma":[0.003904729,0.0001170264,0.0005403269,0.0006899879,0.0001187993,0.0005164295,0.0003636707,0.0007047209,0.0001141203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000366004,"about_ca_system_score_gemma":0.0005904653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005538573,"about_ca_topic_score_gemma":0.005570902,"domain_scores_codex":[0.9996141,0.0001290029,0.00006252919,0.00007896277,0.00008584646,0.00002961963],"domain_scores_gemma":[0.9984101,0.0009227555,0.0002469373,0.00004843084,0.0002744296,0.00009723211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001471947,0.0007862929,0.8514488,0.0002123462,0.0006779512,0.0001755495,0.0001506364,0.01790614,0.002498129,0.0002288386,0.001052571,0.1233909],"study_design_scores_gemma":[0.0000839356,0.001056533,0.4478395,0.00008076011,0.0004337609,0.0003637605,0.0004192088,0.5465651,0.001682987,0.0006898295,0.0007178027,0.00006686361],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9827723,0.0006563925,0.01462672,0.0002636129,0.00009953889,0.00005484147,0.0007975945,0.00005834717,0.0006705628],"genre_scores_gemma":[0.989705,0.000352755,0.008949312,0.00004311109,0.00005082873,0.00004447046,0.0005678133,0.000006354775,0.0002802761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005538573,"threshold_uncertainty_score":0.01101267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06759321884237735,"score_gpt":0.3266333912465099,"score_spread":0.2590401724041326,"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."}}