{"id":"W4214646484","doi":"10.2196/33875","title":"Machine Learning Approach for Preterm Birth Prediction Using Health Records: Systematic Review","year":2022,"lang":"en","type":"review","venue":"JMIR Medical Informatics","topic":"Preterm Birth and Chorioamnionitis","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Systematic review; Receiver operating characteristic; Predictive power; Sample size determination; Population; Descriptive statistics; Machine learning; MEDLINE; Statistics; Artificial intelligence; Computer science; Mathematics","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":[0.0218608,0.001871553,0.009838748,0.01324332,0.0007125159,0.002810641,0.002817606,0.002125565,0.005143592],"category_scores_gemma":[0.1186941,0.001147548,0.01277125,0.01357277,0.0008905139,0.003555858,0.001576833,0.001940657,0.0004112943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004354165,"about_ca_system_score_gemma":0.01342725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01030641,"about_ca_topic_score_gemma":0.01913104,"domain_scores_codex":[0.9746807,0.01161548,0.00799784,0.00148203,0.003862048,0.00036178],"domain_scores_gemma":[0.8612153,0.1147142,0.01656956,0.001733146,0.005397294,0.0003705536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0001769236,0.00003034429,0.002478898,0.935596,0.02481068,0.00005532205,0.0001126976,0.0003191751,0.00003243791,0.0002451063,0.001179674,0.03496262],"study_design_scores_gemma":[0.0003085365,0.0002176954,0.005345911,0.8617873,0.1219725,0.0001897789,0.0001644901,0.0006972236,0.0001178708,0.000604609,0.008531506,0.00006258857],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0010489,0.9962958,0.0005929187,0.000417245,0.0001057034,0.0005932244,0.0007268811,0.00001903601,0.0002003579],"genre_scores_gemma":[0.03478889,0.9581982,0.003347658,0.0007286399,0.0001897744,0.001823691,0.0008109426,0.0000103688,0.0001016717],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.0218608,"threshold_uncertainty_score":0.1156124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07036687548697894,"score_gpt":0.3662404706934431,"score_spread":0.2958735952064641,"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."}}