Endocrinology

Diabetes

Latest AI and machine learning research in diabetes for healthcare professionals.

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Showing 3541-3560 of 4,161 articles

Incorporating Dietary Information to Enhance Polygenic Prediction Models with Applications to Body Mass Index and Type 2 Diabetes

Polygenic predictors can enhance screening for biomedical conditions, such as metabolism-related traits and diseases, but explain limited phenotypic variance and face implementation challenges in non-European populations. On the other hand, dietary quality and other sociocultural factors are well established metabolic risk factors that remain under-investigated in risk stratification models. In th...

Supervoxel-based image-to-biomarker conversions - An initial study on morphological age prediction from whole-body MRI and its clinical relevance in the UK Biobank

Biological aging remains a central focus of research, from the scale of sub-cellular processes to whole-organism tissue morphology and function. In this work, we developed a novel and quantitatively interpretable method for the prediction of variables, such as age, from tomographic medical images. The method uses supervoxels (whose granularity is selected by the user), standardized through inter-s...

A Tabular Residual Neural Network for Diabetes Classification and Prediction

Diabetes Mellitus (DM) is a metabolic disorder characterized by hyperglycemia, with type 1 characterized as an autoimmune destruction of pancreatic be...

ML-Guided GWAS Reveals Genetic Architectures for MASLD for Overweight and Lean Individuals in the All of Us Cohort

Metabolic dysfunction-associated steatotic liver disease (MASLD) arises from excessive hepatic fat accumulation that triggers inflammation and liver i...

Leveraging Pretrained Large Language Model for Prognosis of Type 2 Diabetes Using Longitudinal Medical Records

Timely prognosis of type 2 diabetes (T2D) is critical for effective interventions and reducing economic burden. Longitudinal medical records offer pot...

Early Detection of Cardiovascular Disease Risk Using Multi-Parameter Biomarker Analysis and Machine Learning: A Prospective Cohort Study

Cardiovascular disease (CVD) remains the leading cause of mortality globally, with many events occurring in individuals without prior diagnosed condit...

Hepatic and abdominal adiposity in type 2 diabetes as assessed with machine learning on CT scans

The distribution of abdominal adipose depots and their mechanistic links to type 2 diabetes remain incompletely understood. This study elucidated the ...

Temporal deep learning with clinically engineered biomarkers for the early prediction of type 2 diabetes

Diabetes mellitus remains a major global health burden, causing an estimated 3.4 million deaths in 2024 and highlighting the need for accurate early i...

DRB1 Subtyping Reveals Divergent Risk and Protection for Type 1 Diabetes in Middle Eastern Populations

Type 1 diabetes (T1D) is strongly influenced by HLA variation, yet current genetic risk models developed largely in European cohorts perform suboptima...

Machine Learning-Driven Classification of Type 2 Diabetes Using Gut Microbiome Profiles for Enhanced Detection and Personalised Therapeutics

The purpose of the study is to investigate Type 2 Diabetes Mellitus (T2DM) progression and risk through investigating gut microbiome biomarkers, provi...

Enhancing Early Diabetic Retinopathy Detection through Synthetic DR1 Image Generation: A StyleGAN3 Approach

Diabetic Retinopathy (DR) is a leading cause of preventable blindness. Early detection at the DR1 stage is critical but is hindered by a scarcity of...

A novel approach to finding the compositional differences and biomarkers in gut microbiota in type 2 diabetic patients via meta-analysis, data-mining, and multivariate analysis.

BACKGROUND/PURPOSE OF THE STUDY: Type 2 diabetes mellitus (T2DM)-one of the fastest globally spreading diseases-is a chronic metabolic disorder charac...

Jan 1 2025 40514168
The multikinetic fusion feature of PPG was combined with MCNN_vision_transformer for diabetes detection.

BACKGROUND: Diabetes is a chronic condition that significantly impacts the cardiovascular system and various other organs. Photoplethysmogram (PPG) si...

Jan 1 2025 40535639
Unveiling the molecular mechanisms of stigmasterol on diabetic retinopathy: BNM framework construction and experimental validation.

BACKGROUND: Diabetic retinopathy (DR), one of the most common complications of diabetes, severely impacts patients' quality of life. The combined use ...

Jan 1 2025 40417668
Sex-Specific Ensemble Models for Type 2 Diabetes Classification in the Mexican Population.

BACKGROUND: Type 2 diabetes (T2D) is considered a global pandemic by the World Health Organization (WHO), with a growing prevalence, particularly in M...

Jan 1 2025 40356710
Machine learning with decision curve analysis evaluates nutritional metabolic biomarkers for cardiovascular-kidney-metabolic risk: an NHANES analysis.

BACKGROUND: The American Heart Association recently introduced the concept of Cardiovascular-Kidney-Metabolic Syndrome (CKM), emphasizing the interpla...

Jan 1 2025 40406158
Protocol for evaluating the cost-effectiveness of Mongolia's sugar-sweetened beverages tax using double machine learning.

Elevated consumption of sugar-sweetened beverages (SSBs) has been associated with an increase in obesity, type 2 diabetes, and other non-communicable ...

Jan 1 2025 40493559
Exploring the effect of the triglyceride-glucose index on bone metabolism in prepubertal children, a retrospective study: insights from traditional methods and machine-learning-based bone remodeling prediction.

BACKGROUND: Childhood obesity poses a significant risk to bone health, but the impact of insulin resistance (IR) on bone metabolism in prepubertal chi...

Jan 1 2025 40416622
Machine learning-based coronary heart disease diagnosis model for type 2 diabetes patients.

BACKGROUND: To establish a classification model for assisting the diagnosis of type 2 diabetes mellitus (T2DM) complicated with coronary heart disease...

Jan 1 2025 40475993
SMART (artificial intelligence enabled) DROP (diabetic retinopathy outcomes and pathways): Study protocol for diabetic retinopathy management.

INTRODUCTION: Delayed diagnosis of diabetic retinopathy (DR) remains a significant challenge, often leading to preventable blindness and visual impair...

Jan 1 2025 40388448
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