AIMC Topic: Diabetes Mellitus, Type 2

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Improving Clinical Preparedness: Community Health Nurses and Early Hypoglycemia Prediction in Type 2 Diabetes Using Hybrid Machine Learning Techniques.

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...
Humans Machine Learning Male Middle Aged Diabetes Mellitus, Type 2 Hypoglycemia Nurses, Community Health Algorithms Female Aged Adult
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Development of a machine learning model for precision prognosis of rapid kidney function decline in people with diabetes and chronic kidney disease.

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.
Middle Aged Female Humans Renal Insufficiency, Chronic Disease Progression Risk Factors Machine Learning Glomerular Filtration Rate Diabetes Mellitus, Type 2 Aged Prognosis Diabetic Nephropathies Male Retrospective Studies
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Machine learning and statistical models to predict all-cause mortality in type 2 diabetes: Results from the UK Biobank study.

Diabetes & metabolic syndrome Oct 5, 2024
AIMS: This study aims to compare the performance of contemporary machine learning models with statistical models in predicting all-cause mortality in patients with type 2 diabetes mellitus and to develop a user-friendly mortality risk prediction tool...
Male Middle Aged Diabetes Mellitus, Type 2 Follow-Up Studies Female UK Biobank Models, Statistical Risk Factors Humans Cause of Death Aged Machine Learning Biological Specimen Banks Survival Rate Prospective Studies United Kingdom Prognosis
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Employing Machine Learning Models to Predict Potential α-Glucosidase Inhibitory Plant Secondary Metabolites Targeting Type-2 Diabetes and Their Validation.

Journal of chemical information and modeling Oct 1, 2024
The need for new antidiabetic drugs is evident, considering the ongoing global burden of type-2 diabetes mellitus despite notable progress in drug discovery from laboratory research to clinical application. This study aimed to build machine learning ...
Glycoside Hydrolase Inhibitors Secondary Metabolism Diabetes Mellitus, Type 2 Hypoglycemic Agents Plants alpha-Glucosidases Humans Machine Learning
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Enhancing severe hypoglycemia prediction in type 2 diabetes mellitus through multi-view co-training machine learning model for imbalanced dataset.

Scientific reports Sep 30, 2024
Patients with type 2 diabetes mellitus (T2DM) who have severe hypoglycemia (SH) poses a considerable risk of long-term death, especially among the elderly, demanding urgent medical attention. Accurate prediction of SH remains challenging due to its m...
Glycated Hemoglobin Hypoglycemia Middle Aged Blood Glucose Diabetes Mellitus, Type 2 Hypoglycemic Agents Humans Electronic Health Records Machine Learning Female Algorithms Aged Male
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Predicting diabetes in adults: identifying important features in unbalanced data over a 5-year cohort study using machine learning algorithm.

BMC medical research methodology Sep 27, 2024
BACKGROUND: Imbalanced datasets pose significant challenges in predictive modeling, leading to biased outcomes and reduced model reliability. This study addresses data imbalance in diabetes prediction using machine learning techniques. Utilizing data...
Male Middle Aged Cohort Studies Diabetes Mellitus, Type 2 Female Humans Reproducibility of Results Machine Learning Risk Factors Algorithms Adult
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Predicting Antidiabetic Peptide Activity: A Machine Learning Perspective on Type 1 and Type 2 Diabetes.

International journal of molecular sciences Sep 18, 2024
Diabetes mellitus (DM) presents a critical global health challenge, characterized by persistent hyperglycemia and associated with substantial economic and health-related burdens. This study employs advanced machine-learning techniques to improve the ...
Humans Machine Learning Peptides Diabetes Mellitus, Type 2 Diabetes Mellitus, Type 1 Hypoglycemic Agents Support Vector Machine
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The utility of a machine learning model in identifying people at high risk of type 2 diabetes mellitus.

Expert review of endocrinology & metabolism Sep 8, 2024
BACKGROUND: According to previous reports, very high percentages of individuals in Saudi Arabia are undiagnosed for type 2 diabetes mellitus (T2DM). Despite conducting several screening and awareness campaigns, these efforts lacked full accessibility...
Mass Screening Risk Assessment Saudi Arabia ROC Curve Diabetes Mellitus, Type 2 Adult Female Sensitivity and Specificity Risk Factors Male Aged Middle Aged Humans Machine Learning
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Comparison of Machine Learning Algorithms and Nomogram Construction for Diabetic Retinopathy Prediction in Type 2 Diabetes Mellitus Patients.

Ophthalmic research Sep 4, 2024
INTRODUCTION: The aim of this study was to compare various machine learning algorithms for constructing a diabetic retinopathy (DR) prediction model among type 2 diabetes mellitus (DM) patients and to develop a nomogram based on the best model.
Humans Female Middle Aged Aged Diabetic Retinopathy ROC Curve Cross-Sectional Studies Machine Learning Diabetes Mellitus, Type 2 Male Algorithms Nomograms
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Fully automated epicardial adipose tissue volume quantification with deep learning and relationship with CAC score and micro/macrovascular complications in people living with type 2 diabetes: the multicenter EPIDIAB study.

Cardiovascular diabetology Sep 3, 2024
BACKGROUND: The aim of this study (EPIDIAB) was to assess the relationship between epicardial adipose tissue (EAT) and the micro and macrovascular complications (MVC) of type 2 diabetes (T2D).
Adipose Tissue Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Middle Aged Risk Assessment Deep Learning Diabetes Mellitus, Type 2 Vascular Calcification Computed Tomography Angiography Pericardium Epicardial Adipose Tissue Coronary Artery Disease Adiposity Automation Diabetic Angiopathies Humans Prognosis Female Reproducibility of Results Risk Factors Aged Male
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