{"id":"https://openalex.org/W4283513156","doi":"https://doi.org/10.1055/a-1885-1697","title":"Applying Automated Machine Learning to Predict Mode of Delivery Using Ongoing Intrapartum Data in Laboring Patients","display_name":"Applying Automated Machine Learning to Predict Mode of Delivery Using Ongoing Intrapartum Data in Laboring Patients","publication_year":2022,"publication_date":"2022-06-25","ids":{"openalex":"https://openalex.org/W4283513156","doi":"https://doi.org/10.1055/a-1885-1697","pmid":"https://pubmed.ncbi.nlm.nih.gov/35752169"},"language":"en","primary_location":{"id":"doi:10.1055/a-1885-1697","doi":"https://doi.org/10.1055/a-1885-1697","is_oa":false,"landing_page_url":"https://doi.org/10.1055/a-1885-1697","pdf_url":null,"source":{"id":"https://openalex.org/S82239980","display_name":"American Journal of Perinatology","issn_l":"0735-1631","issn":["0735-1631","1098-8785"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-40","russia-white-list-1"],"host_organization":"https://openalex.org/P4310320000","host_organization_name":"Thieme Medical Publishers (Germany)","host_organization_lineage":["https://openalex.org/P4310320000"],"host_organization_lineage_names":["Thieme Medical Publishers (Germany)"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"American Journal of Perinatology","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036495966","display_name":"Melissa Spring Wong","orcid":"https://orcid.org/0000-0002-8591-9512","observed_orcids":["https://orcid.org/0000-0002-8591-9512"]},"institutions":[{"id":"https://openalex.org/I1282927834","display_name":"Cedars-Sinai Medical Center","ror":"https://ror.org/02pammg90","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1282927834"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Melissa S. Wong","raw_affiliation_strings":["Department of Obstetrics and Gynecology, Cedars-Sinai Medical Center, Los Angeles, California","Division of Informatics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California","Division of Informatics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, United States","Obstetrics and Gynecology, Cedars-Sinai Medical Center Department of Obstetrics and Gynecology, Los Angeles, United States"],"raw_orcid":"https://orcid.org/0000-0002-8591-9512","affiliations":[{"raw_affiliation_string":"Department of Obstetrics and Gynecology, Cedars-Sinai Medical Center, Los Angeles, California","institution_ids":["https://openalex.org/I1282927834"]},{"raw_affiliation_string":"Division of Informatics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California","institution_ids":["https://openalex.org/I1282927834"]},{"raw_affiliation_string":"Division of Informatics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, United States","institution_ids":["https://openalex.org/I1282927834"]},{"raw_affiliation_string":"Obstetrics and Gynecology, Cedars-Sinai Medical Center Department of Obstetrics and Gynecology, Los Angeles, United States","institution_ids":["https://openalex.org/I1282927834"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101145568","display_name":"Matthew Wells","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1282927834","display_name":"Cedars-Sinai Medical Center","ror":"https://ror.org/02pammg90","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1282927834"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew Wells","raw_affiliation_strings":["Enterprise Data Intelligence, Cedars-Sinai Medical Center, Los Angeles, California","Enterprise Data Intelligence, Cedars-Sinai Medical Center, Los Angeles, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Enterprise Data Intelligence, Cedars-Sinai Medical Center, Los Angeles, California","institution_ids":["https://openalex.org/I1282927834"]},{"raw_affiliation_string":"Enterprise Data Intelligence, Cedars-Sinai Medical Center, Los Angeles, United States","institution_ids":["https://openalex.org/I1282927834"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059876162","display_name":"Davina J. Zamanzadeh","orcid":"https://orcid.org/0000-0002-9360-0069","observed_orcids":["https://orcid.org/0000-0002-9360-0069"]},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Davina Zamanzadeh","raw_affiliation_strings":["Medical and Imaging Informatics (MII) Group, Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Medical and Imaging Informatics (MII) Group, Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091601160","display_name":"Samir Akre","orcid":"https://orcid.org/0000-0003-1495-6399","observed_orcids":["https://orcid.org/0000-0003-1495-6399"]},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samir Akre","raw_affiliation_strings":["Medical and Imaging Informatics (MII) Group, Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Medical and Imaging Informatics (MII) Group, Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006799845","display_name":"Joshua M. Pevnick","orcid":"https://orcid.org/0000-0003-0621-1485","observed_orcids":["https://orcid.org/0000-0003-0621-1485"]},"institutions":[{"id":"https://openalex.org/I1282927834","display_name":"Cedars-Sinai Medical Center","ror":"https://ror.org/02pammg90","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1282927834"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joshua M. Pevnick","raw_affiliation_strings":["Division of General Internal Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California","Division of Informatics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California","Division of Informatics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, United States","General Internal Medicine, Cedars-Sinai Medical Center Medicine Department, Los Angeles, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of General Internal Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California","institution_ids":["https://openalex.org/I1282927834"]},{"raw_affiliation_string":"Division of Informatics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California","institution_ids":["https://openalex.org/I1282927834"]},{"raw_affiliation_string":"Division of Informatics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, United States","institution_ids":["https://openalex.org/I1282927834"]},{"raw_affiliation_string":"General Internal Medicine, Cedars-Sinai Medical Center Medicine Department, Los Angeles, United States","institution_ids":["https://openalex.org/I1282927834"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056478657","display_name":"Alex A. T. Bui","orcid":"https://orcid.org/0000-0002-4702-1373","observed_orcids":["https://orcid.org/0000-0002-4702-1373"]},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alex A.T. Bui","raw_affiliation_strings":["Department of Bioengineering, University of California Los Angeles, Los Angeles, California","Medical and Imaging Informatics (MII) Group, Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California","University of California Los Angeles Department of Bioengineering, Los Angeles, United States","University of California Los Angeles Medical Imaging Informatics, Los Angeles, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Bioengineering, University of California Los Angeles, Los Angeles, California","institution_ids":["https://openalex.org/I161318765"]},{"raw_affiliation_string":"Medical and Imaging Informatics (MII) Group, Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California","institution_ids":["https://openalex.org/I161318765"]},{"raw_affiliation_string":"University of California Los Angeles Department of Bioengineering, Los Angeles, United States","institution_ids":["https://openalex.org/I161318765"]},{"raw_affiliation_string":"University of California Los Angeles Medical Imaging Informatics, Los Angeles, United States","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038171106","display_name":"Kimberly D. Gregory","orcid":"https://orcid.org/0000-0003-2313-9200","observed_orcids":["https://orcid.org/0000-0003-2313-9200"]},"institutions":[{"id":"https://openalex.org/I1282927834","display_name":"Cedars-Sinai Medical Center","ror":"https://ror.org/02pammg90","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1282927834"]},{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kimberly D. Gregory","raw_affiliation_strings":["Department of Community Health Sciences, Los Angeles, California Fielding School of Public Health, Los Angeles, California","Department of Obstetrics and Gynecology, Cedars-Sinai Medical Center, Los Angeles, California","Department of Obstetrics and Gynecology, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, California","OB-GYN, Cedars-Sinai Medical Center Department of Obstetrics and Gynecology, Los Angeles, United States","University of California Los Angeles Department of Obstetrics and Gynecology, Los Angeles, United States","University of California Los Angeles Jonathan and Karin Fielding School of Public Health, Los Angeles, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Community Health Sciences, Los Angeles, California Fielding School of Public Health, Los Angeles, California","institution_ids":["https://openalex.org/I161318765"]},{"raw_affiliation_string":"Department of Obstetrics and Gynecology, Cedars-Sinai Medical Center, Los Angeles, California","institution_ids":["https://openalex.org/I1282927834"]},{"raw_affiliation_string":"Department of Obstetrics and Gynecology, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, California","institution_ids":["https://openalex.org/I161318765"]},{"raw_affiliation_string":"OB-GYN, Cedars-Sinai Medical Center Department of Obstetrics and Gynecology, Los Angeles, United States","institution_ids":["https://openalex.org/I1282927834"]},{"raw_affiliation_string":"University of California Los Angeles Department of Obstetrics and Gynecology, Los Angeles, United States","institution_ids":["https://openalex.org/I161318765"]},{"raw_affiliation_string":"University of California Los Angeles Jonathan and Karin Fielding School of Public Health, Los Angeles, United States","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5036495966"],"corresponding_institution_ids":["https://openalex.org/I1282927834"],"apc_list":null,"apc_paid":null,"fwci":3.1029,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.92069438,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"41","issue":"S 01","first_page":"e412","last_page":"e419"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10453","display_name":"Maternal and Perinatal Health Interventions","score":0.7235999703407288,"subfield":{"id":"https://openalex.org/subfields/2729","display_name":"Obstetrics and Gynecology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10453","display_name":"Maternal and Perinatal Health Interventions","score":0.7235999703407288,"subfield":{"id":"https://openalex.org/subfields/2729","display_name":"Obstetrics and Gynecology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.1340000033378601,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.10170000046491623,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mode-of-delivery-prediction","display_name":"mode of delivery prediction","score":0.8700000047683716},{"id":"https://openalex.org/keywords/vaginal-delivery","display_name":"vaginal delivery","score":0.7549999952316284},{"id":"https://openalex.org/keywords/cesarean-section","display_name":"cesarean section","score":0.753000020980835},{"id":"https://openalex.org/keywords/automated-machine-learning","display_name":"automated machine learning","score":0.9340000152587891},{"id":"https://openalex.org/keywords/labor-management","display_name":"labor management","score":0.5099999904632568},{"id":"https://openalex.org/keywords/cervical-dilation","display_name":"cervical dilatation","score":0.8199999928474426},{"id":"https://openalex.org/keywords/electronic-health-record-data","display_name":"electronic health record data","score":0.7149999737739563},{"id":"https://openalex.org/keywords/clinical-decision-support","display_name":"clinical decision support","score":0.7039999961853027}],"concepts":[{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.9375960230827332},{"id":"https://openalex.org/C72563966","wikidata":"https://www.wikidata.org/wiki/Q1303415","display_name":"Cohort","level":2,"score":0.639995813369751},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.6274852156639099},{"id":"https://openalex.org/C167135981","wikidata":"https://www.wikidata.org/wiki/Q2146302","display_name":"Retrospective cohort study","level":2,"score":0.5668556094169617},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5527622699737549},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.509531557559967},{"id":"https://openalex.org/C201903717","wikidata":"https://www.wikidata.org/wiki/Q1778788","display_name":"Cohort study","level":2,"score":0.457794725894928},{"id":"https://openalex.org/C2778408130","wikidata":"https://www.wikidata.org/wiki/Q6679974","display_name":"Vaginal delivery","level":3,"score":0.4425584077835083},{"id":"https://openalex.org/C131872663","wikidata":"https://www.wikidata.org/wiki/Q5284418","display_name":"Obstetrics","level":1,"score":0.4234694540500641},{"id":"https://openalex.org/C194828623","wikidata":"https://www.wikidata.org/wiki/Q2861470","display_name":"Emergency medicine","level":1,"score":0.32791879773139954},{"id":"https://openalex.org/C2779234561","wikidata":"https://www.wikidata.org/wiki/Q11995","display_name":"Pregnancy","level":2,"score":0.24559301137924194},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1834307312965393},{"id":"https://openalex.org/C141071460","wikidata":"https://www.wikidata.org/wiki/Q40821","display_name":"Surgery","level":1,"score":0.17196476459503174},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.11394736170768738},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002585","descriptor_name":"Cesarean Section","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":true},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007743","descriptor_name":"Labor, Obstetric","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011247","descriptor_name":"Pregnancy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012189","descriptor_name":"Retrospective Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012372","descriptor_name":"ROC Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019540","descriptor_name":"Area Under Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D036861","descriptor_name":"Delivery, Obstetric","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D036861","descriptor_name":"Delivery, Obstetric","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":true},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1055/a-1885-1697","doi":"https://doi.org/10.1055/a-1885-1697","is_oa":false,"landing_page_url":"https://doi.org/10.1055/a-1885-1697","pdf_url":null,"source":{"id":"https://openalex.org/S82239980","display_name":"American Journal of Perinatology","issn_l":"0735-1631","issn":["0735-1631","1098-8785"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-40","russia-white-list-1"],"host_organization":"https://openalex.org/P4310320000","host_organization_name":"Thieme Medical Publishers (Germany)","host_organization_lineage":["https://openalex.org/P4310320000"],"host_organization_lineage_names":["Thieme Medical Publishers (Germany)"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"American Journal of Perinatology","raw_type":"journal-article"},{"id":"pmid:35752169","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35752169","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"American journal of perinatology","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.9940000176429749,"display_name":"Good health and well-being"}],"study_designs":[{"id":"https://openalex.org/study-designs/observational-study","display_name":"Observational Study"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1196531273","https://openalex.org/W2012544935","https://openalex.org/W2020894655","https://openalex.org/W2279273215","https://openalex.org/W2312245062","https://openalex.org/W2341671535","https://openalex.org/W2588541500","https://openalex.org/W2767690088","https://openalex.org/W2771270317","https://openalex.org/W2890506437","https://openalex.org/W2986707120","https://openalex.org/W3003328981","https://openalex.org/W3035949602","https://openalex.org/W3048074762","https://openalex.org/W3050094097"],"related_works":["https://openalex.org/W3024677974","https://openalex.org/W4391068584","https://openalex.org/W7204197206","https://openalex.org/W2997700345","https://openalex.org/W4400955960","https://openalex.org/W4410596458","https://openalex.org/W4391068671","https://openalex.org/W7157191910","https://openalex.org/W7165873580","https://openalex.org/W4410319678"],"abstract_inverted_index":{"OBJECTIVE:":[0],"This":[1],"study":[2,38,193],"aimed":[3],"to":[4,13,51,102,120,145,182,293,299,352],"develop":[5],"and":[6,81,147,163,175,205,242,247,261,287,306,309,337],"validate":[7],"a":[8,18,97,122,272,295],"machine":[9],"learning":[10],"(ML)":[11],"model":[12,123,134,317,347],"predict":[14,303],"the":[15,29,82,108,133,137,158,166,173,180,183,192,202,208,222,232,238,254,265,291,342],"probability":[16,270],"of":[17,39,92,132,165,212,228,245,267,269,271,321,323],"vaginal":[19,214,273],"delivery":[20,76,215,274,324],"(Partometer)":[21],"using":[22],"data":[23,286],"iteratively":[24],"obtained":[25],"during":[26,191],"labor":[27,146,304],"from":[28,49,143],"electronic":[30],"health":[31],"record.":[32],"STUDY":[33],"DESIGN:":[34],"A":[35,113,345],"retrospective":[36],"cohort":[37,139,204],"deliveries":[40,190,198],"at":[41,55,140,216],"an":[42],"academic,":[43],"tertiary":[44],"care":[45],"hospital":[46],"was":[47,62,107,118,130,219],"conducted":[48],"2013":[50],"2019":[52],"who":[53],"had":[54],"least":[56],"two":[57],"cervical":[58],"examinations.":[59],"The":[60,86,127],"population":[61,91],"divided":[63],"into":[64],"those":[65,251],"delivered":[66],"by":[67,100,179],"physicians":[68],"with":[69,335],"nulliparous":[70],"term":[71],"singleton":[72],"vertex":[73],"(NTSV)":[74],"cesarean":[75,87,339],"rates":[77,340],"<23.9%":[78,106],"(Partometer":[79],"cohort)":[80],"remainder":[83],"(control":[84],"cohort).":[85],"rate":[88],"among":[89],"this":[90],"lower":[93],"risk":[94],"patients":[95],"is":[96],"standard":[98],"metric":[99],"which":[101,249],"compare":[103],"provider":[104],"rates;":[105],"Healthy":[109],"People":[110],"2020":[111],"goal.":[112],"supervised":[114],"automated":[115,259],"ML":[116,260,288],"approach":[117],"applied":[119],"generate":[121],"for":[124,221,330],"each":[125],"population.":[126,256],"primary":[128],"outcome":[129],"accuracy":[131,266],"developed":[135],"on":[136,281,333],"Partometer":[138,181,203,223,235],"4":[141,217],"hours":[142,218],"admission":[144],"delivery.":[148],"Secondary":[149],"outcomes":[150],"included":[151,200,237],"discrimination":[152],"ability":[153],"(receiver":[154],"operating":[155],"characteristics-area":[156],"under":[157],"curve":[159],"[ROC-AUC]),":[160],"precision-recall":[161],"AUC,":[162],"calibration":[164],"Partometer.":[167],"To":[168],"assess":[169],"generalizability,":[170],"we":[171],"compared":[172],"performance":[174],"clinical":[176,301],"predictors":[177,227],"identified":[178],"control":[184,209,255],"model.":[185],"RESULTS:":[186],"There":[187],"were":[188,199,341],"37,932":[189],"period;":[194],"after":[195],"exclusions,":[196],"9,385":[197],"in":[201,207,231,253,326],"19,683":[206],"cohort.":[210],"Accuracy":[211],"predicting":[213],"87.1%":[220],"(ROC-AUC:":[224],"0.82).":[225],"Clinical":[226],"greatest":[229],"importance":[230],"stacked":[233],"Intrapartum":[234],"Model":[236,240],"Admission":[239],"prediction":[241,268],"ongoing":[243],"measures":[244],"dilatation":[246],"station":[248],"mirrored":[250],"found":[252],"CONCLUSION:":[257],"Using":[258],"intrapartum":[262],"factors":[263],"improved":[264],"over":[275],"both":[276],"previously":[277],"published":[278],"models":[279,331],"based":[280],"logistic":[282],"regression.":[283],"Harnessing":[284],"real-time":[285],"could":[289],"represent":[290],"bridge":[292],"generating":[294],"truly":[296],"prescriptive":[297],"tool":[298],"augment":[300],"decision-making,":[302],"outcomes,":[305],"reduce":[307],"maternal":[308],"neonatal":[310],"morbidity.":[311],"KEY":[312],"POINTS:":[313],"\u00b7":[314,328,344],"Our":[315],"ML-based":[316,346],"yielded":[318],"accurate":[319],"predictions":[320],"mode":[322],"early":[325],"labor..":[327,355],"Predictors":[329],"created":[332],"populations":[334],"high":[336],"low":[338],"same..":[343],"may":[348],"provide":[349],"meaningful":[350],"guidance":[351],"clinicians":[353],"managing":[354]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2022-06-27T00:00:00"}