{"id":"W3016579984","doi":"10.2196/18186","title":"Artificial Intelligence–Based Multimodal Risk Assessment Model for Surgical Site Infection (AMRAMS): Development and Validation Study","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Surgical site infection prevention","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Receiver operating characteristic; Artificial intelligence; Random forest; Medicine; Machine learning; Convolutional neural network; Computer science; Bootstrapping (finance); Risk assessment; Framingham Risk Score; Data mining; Internal medicine","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":[0.007514535,0.001419322,0.0008283652,0.001269629,0.0002920189,0.000838704,0.001273484,0.0008987734,0.001591789],"category_scores_gemma":[0.01257198,0.0003376084,0.001364092,0.0005747476,0.0004328305,0.0007545649,0.001035308,0.001424415,0.0003908217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001208972,"about_ca_system_score_gemma":0.001526548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01065094,"about_ca_topic_score_gemma":0.006354306,"domain_scores_codex":[0.9982917,0.0008994637,0.0001308992,0.0003216009,0.0002428887,0.000113459],"domain_scores_gemma":[0.9917379,0.005661572,0.0004657726,0.0004315554,0.00152167,0.0001814669],"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":[0.001075009,0.001882497,0.1019355,0.0005279505,0.000981251,0.0004102607,0.000236038,0.7098767,0.001991654,0.001969447,0.00524849,0.1738652],"study_design_scores_gemma":[0.00002427652,0.0002885305,0.005160616,0.00003734042,0.00006110309,0.00005239255,0.0000296639,0.9931813,0.0004132043,0.0003964301,0.0003432828,0.00001176281],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8569599,0.001989316,0.133529,0.0007567005,0.0001552962,0.0009168134,0.00182501,0.0008601145,0.003007839],"genre_scores_gemma":[0.9521052,0.0004268533,0.04410357,0.0001298626,0.000035284,0.000417255,0.001962833,0.00002338897,0.0007957317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01065094,"threshold_uncertainty_score":0.03974116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0620017755312087,"score_gpt":0.3784158124483837,"score_spread":0.316414036917175,"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."}}