Diabetes Mellitus, Type 2

Machine learning approaches and genetic determinants that influence the development of type 2 diabetes mellitus: a genetic association study in Brazilian patients.

Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas 39630807

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...

Adult Aged Brazil Case-Control Studies Diabetes Mellitus, Type 2 Female Genetic Association Studies Genetic Predisposition to Disease Genotype Glutathione S-Transferase pi Glutathione Transferase Humans Machine Learning Male Middle Aged Polymorphism, Genetic Polymorphism, Single Nucleotide Risk Factors Vascular Endothelial Growth Factor A

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Enhancing type 2 diabetes mellitus prediction by integrating metabolomics and tree-based boosting approaches.

Frontiers in endocrinology 39588339

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 ...

Adult Aged Algorithms Artificial Intelligence Biomarkers Case-Control Studies Diabetes Mellitus, Type 2 Female Humans Machine Learning Male Metabolomics Middle Aged Prognosis

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Machine learning algorithms mimicking specialists decision making on initial treatment for people with type 2 diabetes mellitus in Japan diabetes data management study (JDDM76).

Diabetes & metabolic syndrome 39644730

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 ...

Aged Algorithms Decision Making Diabetes Mellitus, Type 2 Female Follow-Up Studies Humans Hypoglycemic Agents Japan Machine Learning Male Middle Aged Prognosis Specialization

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Interpretable time-series neural turing machine for prognostic prediction of patients with type 2 diabetes in physician-pharmacist collaborative clinics.

International journal of medical informatics 39626597

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...

Aged Diabetes Mellitus, Type 2 Female Humans Male Middle Aged Neural Networks, Computer Physicians Prognosis

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Mixed-effects neural network modelling to predict longitudinal trends in fasting plasma glucose.

BMC medical research methodology 39707252

BACKGROUND: Accurate fasting plasma glucose (FPG) trend prediction is important for management and treatment of patients with type 2 diabetes mellitus (T2DM), a globally prevalent chronic disease. (Generalised) linear mixed-effects (LME) models and m...

Adult Aged Blood Glucose Diabetes Mellitus, Type 2 Fasting Female Humans Linear Models Longitudinal Studies Machine Learning Male Middle Aged Neural Networks, Computer Prospective Studies

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Modeling the fasting blood glucose response to basal insulin adjustment in type 2 diabetes: An explainable machine learning approach on real-world data.

International journal of medical informatics 39705917

INTRODUCTION: Optimal basal insulin titration for people with type 2 diabetes is vital to effectively reducing the risk of complications. However, a sizeable proportion of people (30-50 %) remain in suboptimal glycemic control six months post-initiat...

Aged Blood Glucose Diabetes Mellitus, Type 2 Fasting Female Humans Hypoglycemic Agents Insulin Machine Learning Male Middle Aged

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Risk prediction of integrated traditional Chinese and western medicine for diabetes retinopathy based on optimized gradient boosting classifier model.

Medicine 39705459

In order to take full advantage of traditional Chinese medicine (TCM) and western medicine, combined with machine learning technology, to study the risk factors and better risk prediction model of diabetic retinopathy (DR), and provide basis for the ...

Adult Aged Diabetes Mellitus, Type 2 Diabetic Retinopathy Female Humans Machine Learning Male Medicine, Chinese Traditional Middle Aged Retrospective Studies Risk Assessment Risk Factors Support Vector Machine

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Potential shared mechanisms in atopic dermatitis and type 2 diabetes identified via transcriptomic and machine learning approaches.

Scientific reports 39681684

Although atopic dermatitis (AD) and type 2 diabetes mellitus (T2DM) may appear clinically and pathophysiologically unrelated, AD is a common skin disease characterized by chronic inflammation and skin barrier dysfunction, whereas T2DM is a metabolic ...

Biomarkers Dermatitis, Atopic Diabetes Mellitus, Type 2 Gene Expression Profiling Humans Machine Learning Receptors, CCR1 Transcriptome

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Multi-Omics Integration With Machine Learning Identified Early Diabetic Retinopathy, Diabetic Macula Edema and Anti-VEGF Treatment Response.

Translational vision science & technology 39671223

PURPOSE: Identify optimal metabolic features and pathways across diabetic retinopathy (DR) stages, develop risk models to differentiate diabetic macular edema (DME), and predict anti-vascular endothelial growth factor (anti-VEGF) therapy response.

Aged Angiogenesis Inhibitors Aqueous Humor Biomarkers Chromatography, High Pressure Liquid Diabetes Mellitus, Type 2 Diabetic Retinopathy Female Humans Lipidomics Machine Learning Macular Edema Male Metabolomics Middle Aged Multiomics Prospective Studies Vascular Endothelial Growth Factor A

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Determinants of developing cardiovascular disease risk with emphasis on type-2 diabetes and predictive modeling utilizing machine learning algorithms.

Medicine 39654201

This research aims to enhance our comprehensive understanding of the influence of type-2 diabetes on the development of cardiovascular diseases (CVD) risk, its underlying determinants, and to construct precise predictive models capable of accurately ...

Adolescent Adult Aged Algorithms Bangladesh Cardiovascular Diseases Diabetes Mellitus, Type 2 Female Humans Hypertension Machine Learning Male Middle Aged Risk Assessment Risk Factors Socioeconomic Factors Young Adult

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Explore the latest research on artificial intelligence and machine learning in medicine.

Machine learning approaches and genetic determinants that influence the development of type 2 diabetes mellitus: a genetic association study in Brazilian patients.

Enhancing type 2 diabetes mellitus prediction by integrating metabolomics and tree-based boosting approaches.

Machine learning algorithms mimicking specialists decision making on initial treatment for people with type 2 diabetes mellitus in Japan diabetes data management study (JDDM76).

Interpretable time-series neural turing machine for prognostic prediction of patients with type 2 diabetes in physician-pharmacist collaborative clinics.

Mixed-effects neural network modelling to predict longitudinal trends in fasting plasma glucose.

Modeling the fasting blood glucose response to basal insulin adjustment in type 2 diabetes: An explainable machine learning approach on real-world data.

Risk prediction of integrated traditional Chinese and western medicine for diabetes retinopathy based on optimized gradient boosting classifier model.

Potential shared mechanisms in atopic dermatitis and type 2 diabetes identified via transcriptomic and machine learning approaches.

Multi-Omics Integration With Machine Learning Identified Early Diabetic Retinopathy, Diabetic Macula Edema and Anti-VEGF Treatment Response.

Determinants of developing cardiovascular disease risk with emphasis on type-2 diabetes and predictive modeling utilizing machine learning algorithms.

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