AIMC Topic: Diabetes, Gestational

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Effects of neonicotinoid pesticide exposure in the first trimester on gestational diabetes mellitus based on interpretable machine learning.

Environmental research
BACKGROUND: Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications and seriously threatens the health of mothers and offspring. Neonicotinoids (NEOs) is a new class of pesticide and widely used worldwide. Prenatal NEOs ...

Prediction of hypertension and diabetes in twin pregnancy using machine learning model based on characteristics at first prenatal visit: national registry study.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
OBJECTIVE: To develop a prediction model for hypertensive disorders of pregnancy (HDP) and gestational diabetes mellitus (GDM) in twin pregnancy using characteristics obtained at the first prenatal visit.

Machine Learning-Based Prediction of Large-for-Gestational-Age Infants in Mothers With Gestational Diabetes Mellitus.

The Journal of clinical endocrinology and metabolism
CONTEXT: Large-for-gestational-age (LGA), one of the most common complications of gestational diabetes mellitus (GDM), has become a global concern. The predictive performance of common continuous glucose monitoring (CGM) metrics for LGA is limited.

Identify gestational diabetes mellitus by deep learning model from cell-free DNA at the early gestation stage.

Briefings in bioinformatics
Gestational diabetes mellitus (GDM) is a common complication of pregnancy, which has significant adverse effects on both the mother and fetus. The incidence of GDM is increasing globally, and early diagnosis is critical for timely treatment and reduc...

Early Prediction of Gestational Diabetes Mellitus in the Chinese Population via Advanced Machine Learning.

The Journal of clinical endocrinology and metabolism
CONTEXT: Accurate methods for early gestational diabetes mellitus (GDM) (during the first trimester of pregnancy) prediction in Chinese and other populations are lacking.

Development and validation of a machine-learning model for prediction of shoulder dystocia.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
OBJECTIVES: To develop a machine-learning (ML) model for prediction of shoulder dystocia (ShD) and to externally validate the model's predictive accuracy and potential clinical efficacy in optimizing the use of Cesarean delivery in the context of sus...

GESTATIONAL DIABETES MELLITUS SEEMS TO BE ASSOCIATED WITH INFLAMMATION.

Acta clinica Croatica
The aim of this study was to investigate whether gestational diabetes mellitus (GDM) is associated with inflammation by comparing serum levels of human chitinase-3-like pro- tein 1 (YKL-40), neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte r...