{"id":"W4281962565","doi":"10.1111/epi.17320","title":"Development and validation of machine learning models for prediction of seizure outcome after pediatric epilepsy surgery","year":2022,"lang":"en","type":"article","venue":"Epilepsia","topic":"Epilepsy research and treatment","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children's Hospital of Eastern Ontario; Western University; Centre Hospitalier Universitaire Sainte-Justine; Public Health Ontario; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Epilepsy; Epilepsy surgery; Concordance; Medicine; Logistic regression; Cohort; Univariate; Magnetic resonance imaging; Confidence interval; Univariate analysis; Retrospective cohort study; Machine learning; Artificial intelligence; Surgery; Multivariate analysis; Internal medicine; Radiology; Multivariate statistics; Computer science; 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":[0.01038036,0.001139203,0.0007967557,0.001491516,0.000349597,0.000856258,0.001002853,0.0006732746,0.000574284],"category_scores_gemma":[0.01707079,0.0002970947,0.0009706675,0.0005727709,0.0003124984,0.0006644061,0.0007655443,0.001079068,0.000320258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008353064,"about_ca_system_score_gemma":0.001484337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003950625,"about_ca_topic_score_gemma":0.002517006,"domain_scores_codex":[0.9972332,0.001607607,0.0002189098,0.0004001757,0.0003750859,0.0001650671],"domain_scores_gemma":[0.9883162,0.007827071,0.001093365,0.0005003408,0.002046551,0.0002164362],"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":[0.0009903165,0.0008394141,0.4144611,0.0001557646,0.0008648022,0.0001808712,0.0001388382,0.4587588,0.002545219,0.0003010804,0.002076431,0.1186873],"study_design_scores_gemma":[0.00003049258,0.0004243474,0.02719486,0.00004836552,0.00006916845,0.00007731176,0.00004262092,0.9699734,0.001608644,0.0002697308,0.0002488957,0.00001225632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.92669,0.0006774866,0.06980721,0.0003465894,0.00005975262,0.0002301638,0.0007292492,0.0005939931,0.0008655416],"genre_scores_gemma":[0.9759302,0.0001143121,0.0224657,0.00004784801,0.00001957127,0.0001496251,0.001021923,0.00001973725,0.0002310644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01038036,"threshold_uncertainty_score":0.05489725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0549756931504512,"score_gpt":0.2878424248628405,"score_spread":0.2328667317123893,"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."}}