Recent applications of machine learning and deep learning models in the prediction, diagnosis, and management of diabetes: a comprehensive review

E Afsaneh, A Sharifdini, H Ghazzaghi… - Diabetology & Metabolic …, 2022 - Springer
Diabetes as a metabolic illness can be characterized by increased amounts of blood
glucose. This abnormal increase can lead to critical detriment to the other organs such as …

Machine learning applied in maternal and fetal health: a narrative review focused on pregnancy diseases and complications

D Mennickent, A Rodríguez, MC Opazo… - Frontiers in …, 2023 - frontiersin.org
Introduction Machine learning (ML) corresponds to a wide variety of methods that use
mathematics, statistics and computational science to learn from multiple variables …

[HTML][HTML] Comparison of machine learning and conventional logistic regression-based prediction models for gestational diabetes in an ethnically diverse population; …

Y Belsti, L Moran, L Du, A Mousa, K De Silva… - International Journal of …, 2023 - Elsevier
Background Early identification of pregnant women at high risk of developing gestational
diabetes (GDM) is desirable as effective lifestyle interventions are available to prevent GDM …

Prediction of gestational diabetes mellitus using machine learning from birth cohort data of the Japan Environment and Children's Study

M Watanabe, A Eguchi, K Sakurai, M Yamamoto… - Scientific reports, 2023 - nature.com
Recently, prediction of gestational diabetes mellitus (GDM) using artificial intelligence (AI)
from medical records has been reported. We aimed to evaluate GDM-predictive AI-based …

Evaluation of first and second trimester maternal thyroid profile on the prediction of gestational diabetes mellitus and post load glycemia

D Mennickent, B Ortega-Contreras, S Gutiérrez-Vega… - PloS one, 2023 - journals.plos.org
Maternal thyroid alterations have been widely associated with the risk of gestational
diabetes mellitus (GDM). This study aims to 1) test the first and the second trimester full …

Prediction of gestational diabetes mellitus in Asian women using machine learning algorithms

BS Kang, SU Lee, S Hong, SK Choi, JE Shin, JH Wie… - Scientific Reports, 2023 - nature.com
This study developed a machine learning algorithm to predict gestational diabetes mellitus
(GDM) using retrospective data from 34,387 pregnancies in multi-centers of South Korea …

Explainable artificial intelligence-driven gestational diabetes mellitus prediction using clinical and laboratory markers

V Vivek Khanna, K Chadaga, N Sampathila… - Cogent …, 2024 - Taylor & Francis
Gestational diabetes is characterized by hyperglycemia diagnosed during pregnancy. High
blood sugar levels are likely to affect both the mother and child. This disease frequently goes …

Integration of clinical demographics and routine laboratory analysis parameters for early prediction of gestational diabetes mellitus in the Chinese population

H Zhang, J Dai, W Zhang, X Sun, Y Sun… - Frontiers in …, 2023 - frontiersin.org
Gestational diabetes mellitus (GDM) is one of the most common complications in pregnancy,
impairing both maternal and fetal health in short and long term. As early interventions are …

Glu-Ensemble: An ensemble deep learning framework for blood glucose forecasting in type 2 diabetes patients

Y Han, DY Kim, J Woo, J Kim - Heliyon, 2024 - cell.com
Diabetes is a chronic metabolic disorder characterized by elevated blood glucose levels,
posing significant health risks such as cardiovascular disease, and nerve, kidney, and eye …

Prediction of gestational diabetes mellitus in the first trimester of pregnancy based on maternal variables and pregnancy biomarkers

A Tranidou, I Tsakiridis, A Apostolopoulou, T Xenidis… - Nutrients, 2023 - mdpi.com
Gestational diabetes mellitus (GDM) is a significant health concern with adverse outcomes
for both pregnant women and their offspring. Recognizing the need for early intervention …