{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002839923,0.0006759961,0.005239437,0.0003716342,0.000383775,0.00005544595,0.0005073692,0.0005142076,0.0005552173],"category_scores_gemma":[0.001576245,0.0004907497,0.001079103,0.0006234022,0.00008794454,0.0002079125,0.00023756,0.002210803,0.00001723836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007816207,"about_ca_system_score_gemma":0.002118802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009489349,"about_ca_topic_score_gemma":5.584586e-7,"domain_scores_codex":[0.9927106,0.0005441246,0.003997939,0.0003248328,0.001709644,0.0007128092],"domain_scores_gemma":[0.9953463,0.0003914854,0.002517513,0.0007616486,0.00009412369,0.0008889436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009200739,0.00005978935,0.000001830794,0.8069794,0.000233371,0.000005644934,0.0002769757,5.126654e-7,7.658551e-10,0.00001477727,0.001151934,0.1912666],"study_design_scores_gemma":[0.0004571359,0.0004591818,5.618713e-8,0.4386811,0.001540665,0.001416819,0.0001048405,0.01774121,6.466695e-9,0.000002125879,0.5393568,0.0002400989],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[4.093806e-7,0.9783678,0.005238408,0.00004510761,0.000422045,0.01377782,0.000442546,0.0002799169,0.001425925],"genre_scores_gemma":[4.957204e-7,0.9821574,0.004499702,0.001900912,0.0003678281,0.004241441,0.006279801,0.000112678,0.0004397621],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.5382048,"threshold_uncertainty_score":0.9997544,"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."}}