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Pregnancy in Obesity

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Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study.

Journal of diabetes research 32626780
BACKGROUND: Gestational diabetes mellitus (GDM) contributes to adverse pregnancy and birth outcomes. In recent decades, extensive research has been devoted to the early prediction of GDM by various methods. Machine learning methods are flexible predi...
Adult Blood Glucose Cholesterol Clinical Decision Rules Cohort Studies Decision Trees Diabetes, Gestational Female Glycated Hemoglobin Humans Lipoproteins, HDL Logistic Models Machine Learning Maternal Age Pregnancy Pregnancy in Obesity Reproducibility of Results Retrospective Studies Routinely Collected Health Data Triglycerides Uric Acid Young Adult
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Prediction of obstetrical and fetal complications using automated electronic health record data.

American journal of obstetrics and gynecology 33098815
An increasing number of delivering women experience major morbidity and mortality. Limited work has been done on automated predictive models that could be used for prevention. Using only routinely collected obstetrical data, this study aimed to devel...
Adult Blood Pressure Clinical Decision Rules Electronic Health Records Female Humans Hypoxia-Ischemia, Brain Machine Learning Maternal Age Obstetric Labor Complications Parity Postpartum Hemorrhage Pre-Eclampsia Pregnancy Pregnancy in Obesity Premature Birth Reproducibility of Results Retrospective Studies Routinely Collected Health Data Stillbirth Time Factors Uterine Rupture
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