Predicting recurrent gestational diabetes mellitus using artificial intelligence models: a retrospective cohort study.

Journal: Archives of gynecology and obstetrics

PMID: 39080058

Abstract

BACKGROUND: We aimed to develop novel artificial intelligence (AI) models based on early pregnancy features to forecast the likelihood of recurrent gestational diabetes mellitus (GDM) before 14 weeks of gestation in subsequent pregnancies.

Authors

Min Chen

School of Computer Science and TechnologyHuazhong University of Science and Technology Wuhan 430074 China.
Weijiao Xu

Zhangzhou Health Vocational College, Zhangzhou, China.
Yanni Guo

Department of Obstetrics and Gynecology, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University Fujian Maternity and Child Health Hospital, Fuzhou, China.
Jianying Yan

Department of Obstetrics and Gynecology, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University Fujian Maternity and Child Health Hospital, Fuzhou, China. yanjy2019@fjmu.edu.cn.

Keywords

Adult Algorithms Artificial Intelligence Cohort Studies Decision Trees Diabetes, Gestational Female Humans Logistic Models Pregnancy Recurrence Retrospective Studies Support Vector Machine

External Resources

View on PubMed Access via DOI PubMed (39080058)

Predicting recurrent gestational diabetes mellitus using artificial intelligence models: a retrospective cohort study.

Abstract

Authors

Keywords

External Resources

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