Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas
Dec 2, 2024
This genetic association study including 120 patients with type 2 diabetes mellitus (T2DM) and 166 non-diabetic individuals aimed to investigate the association of polymorphisms in the genes GSTM1 and GSTT1 (gene deletion), GSTP1 (rs1695), ACE (rs464...
International journal of medical informatics
Nov 29, 2024
BACKGROUND: Type 2 diabetes (T2D) has become a serious health threat globally. However, the existing approaches for diabetes prediction mainly had difficulty in addressing multiple time-series features. This study aims to provide an adjunctive tool f...
OBJECTIVE: To evaluate whether typical machine learning models that mimic specialists' care can successfully reproduce information, not only on whether to prescribe medications but also which hypoglycemic agents to prescribe as initial treatment for ...
BACKGROUND AND AIMS: To prevent end-stage renal disease caused by diabetic kidney disease, we created a predictive model for high-risk patients using machine learning.
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a global health problem characterized by insulin resistance and hyperglycemia. Early detection and accurate prediction of T2DM is crucial for effective management and prevention. This study explores the ...
BACKGROUND: Type II diabetes mellitus (T2DM) is strongly linked with a heightened risk of coronary artery disease (CAD). Exploring biological targets common to T2DM and CAD is essential for CAD intervention strategies.
Frontiers in cellular and infection microbiology
Nov 4, 2024
BACKGROUND: This study aimed to characterize the oral and gut microbiota in prediabetes mellitus (Pre-DM) and type 2 diabetes mellitus (T2DM) patients while exploring the association between tongue manifestations and the oral-gut microbiota axis in d...
This study aimed to construct a high-performance prediction and diagnosis model for type 2 diabetic retinopathy (DR) and identify key correlates of DR. This study utilized a cross-sectional dataset of 3,000 patients from the People's Liberation Army ...
Public health nursing (Boston, Mass.)
Oct 22, 2024
OBJECTIVES: The aim of the study was to analyze the data of diabetic patients regarding warning signs of hypoglycemia to predict it at an early stage using various novel machine learning (ML) algorithms. Individual interviews with diabetic patients w...
Diabetes research and clinical practice
Oct 19, 2024
AIMS: To develop a machine learning model for predicting rapid kidney function decline in people with type 2 diabetes (T2D) and chronic kidney disease (CKD) and to pinpoint key modifiable risk factors for targeted interventions.
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