Diabetes

Risk prediction in IgA nephropathy: from conventional models to machine learning, deep learning, and precision nephrology.

IgA nephropathy (IgAN) is the most prevalent primary glomerular disease worldwide and a leading cause of end-stage kidney disease (ESKD). Its clinical heterogeneity results in divergent renal outcomes, making early identification of high-risk patients essential. Prognostic models are crucial for stratifying ESKD risk, guiding treatment intensity, optimizing timing of interventions such as immunosu...

Readability, Accuracy, and Lexical Diversity of New ChatGPT Models for Common Carpal Tunnel Syndrome Questions.

BACKGROUND: Carpal tunnel syndrome (CTS) is a prevalent neuropathy in hand surgery that significantly affects people's quality of life. Frequently, patients conduct research online before seeking medical care. Large language models (LLMs) like ChatGPT are increasingly used for health information, yet concerns remain regarding the accuracy, readability, and complexity of their responses. Previous s...

Factors Associated with Machine Learning-Based Predictions of Retinal Aging Using Teleretinal Screening Images from Patients with Diabetes.

PURPOSE: To identify factors associated with accelerated retinal aging based on machine learning predictions of age using fundus images from teleretin...

The Burden of Delayed Diabetic Retinopathy Management and Use of Artificial Intelligence-Driven Screening Tools: A Systematic Literature Review.

PURPOSE: Patients with diabetic retinopathy (DR) are at risk of visual deterioration owing to systemic and financial barriers in accessing appropriate...

Machine learning-assisted multi-aptamer encoding enables pattern-level discrimination of HbA1c in complex biological matrices.

AMP-CapsNet: a multi-view feature fusion approach for antimicrobial peptide prediction using capsule networks.

Antimicrobial peptides (AMPs) are universally found in both intracellular and extracellular settings and have significant antibiotic-resistant bacteri...

Simultaneous Segmentation of Geographic Atrophy in Longitudinally Acquired Fundus Autofluorescence Images.

PURPOSE: Accurately measuring geographic atrophy (GA) progression in clinical trials is challenging, owing to its slow and variable nature. This study...

Letter: Deep Learning Model Significantly Improves MAGGIC Score for Predicting Contrast-Induced Nephropathy in STEMI Patients.

Developing and validating a machine learning model for predicting post-thrombolysis seizures in acute ischemic stroke.

Post-stroke seizures (PSS) manifests variably due to ischemic brain injury, yet its risk factors remain unclear. This study developed a machine learni...

Development of an explainable machine learning model for predicting depression in adults with type 2 diabetes mellitus: A cross-sectional SHAP-based analysis of NHANES 2009-2023.

Depression (DEP) is a common yet underdiagnosed comorbidity in adults with type 2 diabetes mellitus (T2DM), worsening glycemic control and increasing ...

Predictors of Glycemic Response to Sulfonylurea Therapy in Type 2 Diabetes Over 12 Months: Comparative Analysis of Linear Regression and Machine Learning Models.

BACKGROUND: Sulfonylureas are commonly prescribed for managing type 2 diabetes, yet treatment responses vary significantly among individuals. Although...

Real-world performance of an AI system for diabetic retinopathy screening.

Diabetic retinopathy (DR) is a leading cause of preventable blindness, and the growing global burden of diabetes is placing increasing pressure on oph...

Intravitreal faricimab in patients with refractory diabetic macular edema: 6-month fluid analysis using artificial intelligence.

PURPOSE: Diabetic macular edema (DME) is a leading cause of vision loss in patients with diabetes. In developed countries, intravitreal (IVT) anti-vas...

Comparison of the predictive power of novel insulin resistance, lipid metabolism and obesity indices for the risk of developing dyslipidaemia in adults.

The future of PCOS management: Disease modification through regenerative, metabolic, and digital therapeutics.

Polycystic ovary syndrome (PCOS) represents the leading endocrine problem affecting women of reproductive age, leading to serious complications relate...

Salivary extracellular vesicles and Raman spectroscopy in precision diagnostics of type 2 diabetes.

Type 2 Diabetes (T2D) remains a major global health issue, driven by sedentary lifestyles and aging populations, emphasizing the urgent need for preci...

Synergistic impact of Gram-negative bacterial co-infection on invasive pulmonary aspergillosis in non-neutropenic patients: a machine learning-based risk stratification approach.

BACKGROUND: Invasive pulmonary aspergillosis (IPA) is increasingly recognized in non-neutropenic patients, where coexisting bacterial infections, part...

TrkA abundance is increased in cutaneous nerves in bortezomib-induced neuropathy.

Tropomyosin receptor kinase A (TrkA), a high-affinity receptor for nerve growth factor (NGF), is implicated in nociception and local angiogenesis. We ...

Integrating Regenerative Therapies and Artificial Intelligence for Precision Management of Diabetic Foot Ulcers.

SIGNIFICANCE: Diabetic foot ulcers (DFUs) represent one of the most devastating complications of diabetes, leading to high rates of amputation and mor...

Temporal machine learning framework for diabetic foot ulcer healing trajectory prediction.

OBJECTIVES: Diabetic foot ulcer management relies predominantly on reactive treatment adjustments based on current wound status. This study developed ...