Diabetes

Type 2 Diabetes Mellitus Remission, Dream or Reality? A Narrative Review of Current Evidence and Integrated Care Strategies.

Type 2 diabetes mellitus (T2DM) is a global health priority, with an estimated 629 million people pr...

Micropore array-based SERS sensor assisted by convolutional neural networks for subsurface biotoxic-free detection of interstitial fluid in bioassays.

Accurate and sensitive detection of small-molecule metabolites such as uric acid, glucose, and lacti...

Commentary on "Photodiagnosis with deep learning: A GAN and autoencoder-based approach for diabetic retinopathy detection" by Gencer et al., 2025.

Construction of a PANoptosis-Related Gene Signature for Diabetic Nephropathy.

INTRODUCTION: Diabetic nephropathy (DN) is a serious complication of diabetes. In this study, we aim...

Task Augmentation-Based Meta-Learning Segmentation Method for Retinopathy.

Deep learning (DL) requires large amounts of labeled data, which is extremely time-consuming and lab...

Adipose-Derived Mesenchymal Stem Cells Accelerate Diabetic Foot Ulcer Healing by Promoting Macrophage M2 Polarization Through Downregulation of and .

PURPOSE: Macrophage polarization plays a critical role in the chronic wound healing of diabetic foot...

Preventive and therapeutic strategies via health care delivery system to minimize sight-threatening diabetic retinopathy: a narrative review.

PURPOSE OF REVIEW: To highlight various preventive and therapeutic strategies via health care delive...

Direct-to-Consumer Testing: Relevance for Diabetes Therapy.

The performance of laboratory measurements by the people with diabetes (PwD) themselves ("direct-to-...

Disparate Model Performance and Stability in Machine Learning Clinical Support for Diabetes and Heart Diseases.

Machine Learning (ML) algorithms are vital for supporting clinical decision-making in biomedical inf...

Fully Wearable Devices for Real-Time Health Monitoring and Multimodal Sensing in Nanomedicine Using Multiplexed Green Biofuels.

Fully wearable devices are crucial for real-time health monitoring, but existing devices often lack ...

Identification of macrophage-associated diagnostic biomarkers and molecular subtypes in gestational diabetes mellitus based on machine learning.

Gestational diabetes mellitus (GDM) is a common metabolic disorder during pregnancy, involving multi...

Association of urinary metal elements with sarcopenia and glucose metabolism abnormalities: Insights from NHANES data using machine learning approaches.

BACKGROUND: Sarcopenia, a condition marked by the decline of skeletal muscle mass and function, is p...

Chemical Properties-Based Deep Learning Models for Recommending Rational Daily Diet Combinations to Diabetics Through Large-Scale Virtual Screening of α-Glucosidase Dietary-Derived Inhibitors and Verified In Vitro.

The lack of suitable chemical research methodologies has hindered the discovery of rational daily di...

Case-control study combined with machine learning techniques to identify key genetic variations in GSK3B that affect susceptibility to diabetic kidney diseases.

The role of genetic susceptibility in early warning and precise treatment of diabetic kidney disease...

Prediction and accuracy improvement of insulin pump in-fusion deviation based on LSTM and PID.

In order to further improve the injection precision of the PH300 insulin pump, this paper optimizes ...

Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis.

Diabetes Mellitus is a chronic metabolic disorder affecting a substantial global population leading ...

Out-of-distribution reject option method for dataset shift problem in early disease onset prediction.

Machine learning is increasingly used to predict lifestyle-related disease onset using health and me...

DiaBD: A diabetes dataset for enhanced risk analysis and research in Bangladesh.

Diabetes is a chronic condition affecting millions worldwide and severely impacts health and quality...

Assessing the stress hyperglycemia ratio in hyperlipidemia patients to predict all-cause mortality: A retrospective cohort study.

BACKGROUND: The Stress Hyperglycemia Ratio (SHR) reflects stress-related hyperglycemia and is linked...

The Application of Machine Learning in Warfarin Dose Precision for Diabetic Patients Treated with Statins: A Comparative Study.

PURPOSE: To evaluate the impact of statin therapy on warfarin dose requirements in diabetic patients...

Revolutionizing diabetes care: the role of artificial intelligence in prevention, diagnosis, and patient care.

UNLABELLED: Millions of people worldwide have diabetes, a disease that is becoming more common and h...