Diabetes

Aging-driven transcriptional programs in diabetic kidney disease: multi-omics discovery of diagnostic biomarkers and drug-repurposing targets.

BACKGROUND: Diabetic kidney disease (DKD) is the primary global cause of end-stage renal disease. However, the aging-related gene networks driving its progression remain unclear. METHODS: In this study, we integrated bioinformatics and experiments to screen for age-related hub genes in DKD and explore their diagnostic and therapeutic values. Transcriptomic datasets and aging-related gene databases...

Natural language processing identifies symptoms predicting complete coronary artery occlusion in patients with NSTEMI.

AIMS: One in 10 patients present to the emergency department (ED) with symptoms of acute coronary syndrome (ACS). The 13-item ACS Symptom Checklist is a validated tool for rapid ACS symptom assessment. We aimed to evaluate the effectiveness of the 13-item ACS Symptom Checklist in distinguishing NSTEMI patients with and without an occluded artery using natural language processing (NLP). METHODS AND...

A hybrid model for early diagnosis of ophthalmology diseases leveraging CNNs, SBOA optimization, and XAI for visualization.

Ophthalmology diseases are among the leading causes of vision loss worldwide. Glaucoma, diabetic retinopathy, and cataracts are the most common diseas...

The Triglyceride Glucose-a Body Shape Index: A Novel Composite Index for Prediction of Periodontitis Risk.

INTRODUCTION AND AIM: Insulin resistance and obesity are significant metabolic risk factors for periodontitis. This study aimed to systematically inve...

Machine learning evaluation of clinical, social and behavioural factors influencing progression from pre-diabetes to type 2 diabetes: a retrospective cohort study in southeast Michigan.

OBJECTIVE: We aimed to use machine learning (ML) models to investigate the impact of clinical, social and behavioural factors on 1-year progression fr...

Behavior Change Content and Implementation of Large Language Model-Driven Conversational Agents in Cardiometabolic Care: Scoping Review.

BACKGROUND: Large language models (LLMs) are increasingly embedded in conversational agents for cardiometabolic care. These systems could support self...

Prevalence of hypertension and diabetes in Bangladesh: identifying gaps in awareness and misinformation.

OBJECTIVE: Non-communicable diseases (NCDs) are a growing health burden in low- and middle-income countries, with hypertension and poor glycaemic cont...

Assessing the readability of AI-generated medication counseling for common Medicaid drug classes: metformin, lisinopril, and atorvastatin.

BACKGROUND: Metformin, lisinopril, and atorvastatin rank among the most commonly prescribed medications for Medicaid patients; however, patients often...

Assessing Quality, Readability, and Transparency of Online and AI-Generated Information on Type 2 Diabetes Mellitus: Cross-Sectional Exploratory Study.

BACKGROUND: Type 2 diabetes mellitus (T2DM) affects approximately 590 million people worldwide, and its management relies heavily on patient education...

Interpretable machine learning for predicting mild cognitive impairment in elderly patients with type 2 diabetes mellitus: model development and performance assessment.

Type 2 diabetes mellitus (T2DM) is a prevalent chronic condition, particularly in the elderly, and is associated with an increased risk of cognitive d...

Explainable Machine-Learning Model for Predicting Severe Obstructive Sleep Apnea in Patients Undergoing Metabolic Bariatric Surgery.

BACKGROUND: Severe obstructive sleep apnea (SOSA) is associated with an increased risk of perioperative complications in patients undergoing metabolic...

A framework for assessing algorithmic discrimination risks in training data: a case of pediatric type 1 diabetes.

OBJECTIVES: To develop a generalizable framework for identifying algorithmic discrimination risks arising from subgroup imbalances in machine learning...

Association of Variability of Monthly Continuous Glucose Monitoring-Derived Metrics With Diabetic Kidney Disease in Type 1 Diabetes.

BACKGROUND: While HbA1c is the standard for monitoring long-term glycaemic control, it fails to capture glycaemic variability. We investigated the dis...

A pH-Calibrated Multi-Analyte MXene Aerogel Electrochemical Platform Assisted by Interpretable Machine Learning for CSF-Based Prescreening of Postoperative Bacterial Meningitis.

Rapid and reliable prescreening and early risk stratification of postoperative meningitis (PNM) remain challenging because clinical symptoms are nonsp...

Interpretable machine learning models predict cognitive impairment in adults aged 50 and over with diabetes: influence of dietary nutrients.

Introduction: diabetes mellitus increases the risk of cognitive impairment, but the role of dietary nutrients remains unclear. Objectives: to develop ...

Artificial Intelligence in Neonatal Care: The Breadth of Promise, the Depth of Challenge-An Overview.

Artificial intelligence (AI) is becoming an integral tool in clinical care. The recent position statement by the Royal Australasian College of Physici...

Individualised treatment effects of corticosteroids in IgA nephropathy.

BACKGROUND: IgA nephropathy (IgAN) has diverse clinical presentations and responses to treatment. For systemic corticosteroids in particular, randomis...

Prism-refraction K-means polar lights optimizer-driven feature selection for accurate diabetes diagnosis.

This study developed a machine learning framework for stratifying abnormal glucose tolerance risk among outpatients presenting with foamy urine. It re...

An AI-Assisted Tool to Predict Continuous Glucose Monitor Adherence in Children With Type 1 Diabetes in Oman: Protocol for a Multiphase Mixed Methods Translational Study.

BACKGROUND: Type 1 diabetes mellitus (T1DM) in children requires sustained self-management to achieve glycemic targets. Continuous glucose monitoring ...

Interpretable single-cell machine learning identifies PINK1-centred mitophagy as a determinant of metabolic fitness in type 2 diabetes.

BACKGROUND: Progressive pancreatic β-cell dysfunction constitutes a hallmark of type 2 diabetes (T2D), yet the molecular programmes governing metaboli...