Primary Care

Multi-modal AI for opportunistic screening, staging and progression risk stratification of steatotic liver disease.

The global rise in steatotic liver disease poses a significant public health challenge. While non-contrast computed tomography scans hold promise for opportunistic detection of steatotic liver disease, their potential for staging and risk assessment remains underexplored. Here we present a multimodal AI model trained on a large dataset, comprising of (n=968) histopathologically and (n=1103) radiol...

Machine learning based identification of key predictors and socioeconomic inequalities in the co-existence of diabetes and hypertension among Bangladeshi adults.

Periodontitis Prediction Model Using Linked Electronic Health and Dental Records.

INTRODUCTION: Periodontal disease (PD) is closely linked to systemic health, with established associations with chronic conditions (eg, diabetes, card...

Molecular docking approaches in mycetoma: Toward improved patient management.

Mycetoma is a neglected tropical disease characterised by chronic, granulomatous inflammation of the subcutaneous tissues, often leading to disfigurem...

Metabolomics-guided machine learning reveals diagnostic and mechanistic biomarkers in CHB with MASLD.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) often coexists with chronic hepatitis B (CHB), yet early diagnosis remain...

Long-Term Caregivers' Perceptions and Expectations Toward the Use of Nursing Robots: A Meta-Synthesis of Qualitative Research.

This study aims to synthesize the perceptions and expectations of long-term caregivers regarding the use of nursing robots to inform strategies for en...

Detection of esophageal varices and prediction of hepatic decompensation in unresectable hepatocellular carcinoma using AI.

BACKGROUND & AIMS: In hepatocellular carcinoma (HCC) with cirrhosis, portal hypertension worsens outcomes. Esophagogastroduodenoscopy (EGD), the curre...

Limitation of existing GFR estimating equations and application of artificial intelligence in improving GFR estimation and chronic kidney disease progression in people with diabetes.

The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2009 equation is the most commonly used equation for estimating glomerular filtration ...

Data-driven subgroups for 3-year risk stratification of incident diabetes and complications in diabetes-free Chinese adults.

BACKGROUND: Substantial metabolic heterogeneity exists prior to the development of diabetes, creating opportunities for earlier and more precise inter...

Smartphone-Based Portable Slit Lamp in Anterior Segment Diseases: A Narrative Review of Clinical Assessment and Integration with Artificial Intelligence.

Smartphone-based portable slit lamps are rapidly evolving from simple add-ons into practical, low-cost front-line tools for anterior segment care beyo...

Enhanced diabetes prediction using pre-trained CNNs, LSTM, and conditional GAN on transformed numerical data.

Diabetes remains a major public health challenge, contributing to complications such as kidney disease, cardiovascular disorders, and diabetic retinop...

The use of the odds ratio product and self-reported data to detect comorbid insomnia and sleep apnea.

STUDY OBJECTIVES: To evaluate the utility of the odds ratio product (ORP) in differentiating comorbid insomnia and sleep apnea (COMISA) from obstructi...

Health-oriented sleep states: making sleep states reflect health conditions.

STUDY OBJECTIVES: The rich information in sleep offers insights into brain function and overall health. The current guidelines for sleep staging by th...

Machine-learning-derived phenotypes of hypertensive patients using multidimensional clinical and echocardiographic data including strain imaging.

AIMS: We applied unsupervised machine learning clustering to a large cohort of hypertensive patients undergoing echocardiography with strain imaging t...

Current and future use of artificial intelligence in valvular heart disease imaging.

Valvular heart disease (VHD) remains significantly underdiagnosed and undertreated. This review examines an artificial intelligence (AI)-enhanced 'spo...

Prediction of metabolically healthy obesity based on dietary nutrients: a comparative analysis of six machine learning models with SHAP and LIME interpretation.

PURPOSE: The relationship between dietary nutrient intake and metabolically healthy obesity (MHO) remains poorly understood. This study aimed to const...

Cardiovascular Risk Assessment Tools in Chronic Kidney Disease.

Cardiovascular (CV) risk calculators estimate the likelihood of CV events by integrating factors such as age, sex, blood pressure, lipids, smoking, an...

Memristive Reservoir Computing Circuit for Real-Time Prediction of Epilepsy.

The prediction of epileptic seizures can significantly improve patients' quality of life by enabling timely preventive interventions. However, realizi...

Personalized Diabetes Treatment Support Using Large Language Models Fine-Tuned on Electronic Health Records: Development and Evaluation Study.

BACKGROUND: Effective diabetes management requires individualized treatment strategies tailored to patients' clinical characteristics. With recent adv...

Explainable AI-based analysis of human pancreas sections identifies traits of type 2 diabetes.

Type 2 diabetes (T2D) is a chronic disease currently affecting around 500 million people worldwide with often severe health consequences. Yet, histopa...