Enhancing gestational diabetes mellitus risk assessment and treatment through GDMPredictor: a machine learning approach.

ABSTRACT:

Background

Gestational diabetes mellitus (GDM) is a serious health concern that affects pregnant women worldwide and can lead to adverse pregnancy outcomes. Early detection of high-risk individuals and the implementation of appropriate treatment can enhance these outcomes.

Methods

We conducted a study on a cohort of 3467 pregnant women during their pregnancy, with a total of 5649 clinical and biochemical records collected. We utilized this dataset as our training dataset to develop a web server called GDMPredictor. The GDMPredictor utilizes advanced machine learning techniques to predict the risk of GDM in pregnant women. We also personalize treatment recommendations based on essential biochemical indicators, such as A1MG, BMG, CysC, CO2, TBA, FPG, and CREA. Our assessment o

SUBMITTER: Xing J 

PROVIDER: S-EPMC11369014 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature