Primary Care

GlucoseGo: a simple tool to predict hypoglycaemia during exercise in type 1 diabetes.

AIMS/HYPOTHESIS: This study aimed to develop an accessible tool, derived using machine learning, to predict hypoglycaemia risk at the start of exercise and to provide clear, rapid risk assessment to support safer participation in exercise. METHODS: Data from four diverse studies were combined, encompassing 16,430 exercise sessions from 834 participants aged 12-80 years using various insulin delive...

Integrating trust into artificial intelligence for medicine: using diabetes as the exemplar disease.

Retinal BioAge is associated with indicators of cardiovascular-kidney-metabolic syndrome in UK and US populations.

Accelerated biological aging, as well as cardiovascular, kidney, and metabolic (CKM) diseases, contribute to shortened healthspan. We studied a deep-l...

Integrated virtual screening, machine learning and molecular dynamics identify novel phytochemical FabI inhibitors against MRSA.

Methicillin-resistant Staphylococcus aureus (MRSA) infections pose a critical global health threat, necessitating the discovery of novel antibacterial...

EASDnet: Empowering human-centered evidence-based medicine through an evidence and attention-based spatial disparity network for discriminative colorectal cancer histopathological screening and attribution.

PURPOSE: Accurate preoperative staging of colorectal cancer is critical to guide treatment decisions, including eligibility for R0 resection, to reduc...

Screening for Breast Cancer: Imaging Updates.

This article provides a comprehensive overview of breast cancer screening guidelines and the evolving role of established and emerging imaging technol...

Integrative metabolomics and machine learning reveal the toxic mechanisms of elaidic acid in polycystic ovary syndrome.

BACKGROUND: Polycystic ovary syndrome (PCOS) is characterized by reproductive dysfunction and metabolic disturbances, including obesity, insulin resis...

Integrative network toxicology and molecular docking preliminarily explore the potential role of polystyrene microplastics in childhood obesity.

Childhood obesity is a severe global epidemic, and emerging evidence suggests environmental pollutants like polystyrene microplastics (PS-MPs) may dis...

Which of the five anthropometric and lipid-based indexes best predicts hypertension? A machine learning approach.

Hypertension is associated with anthropometric and lipid-based indexes. This study aimed to examine and compare the predictive performance of these in...

Predicting Hypertension Persistence in Coarctation of the Aorta: A Feasibility Study.

Hypertension (HTN), despite contemporary endovascular repair, is a common and challenging complication of coarctation of the aorta (CoA), and its mech...

Generative artificial intelligence in dementia care: a scoping review protocol on nursing roles, experiences and ethical perspectives.

INTRODUCTION: Generative artificial intelligence (GAI), including large language models and multimodal generative systems, is rapidly emerging in heal...

Longitudinal multisource clinical model for early lung cancer risk stratification and screening.

OBJECTIVES: Lung cancer is the leading cause of cancer-related mortality worldwide, with poor prognosis largely due to late-stage diagnosis. Current s...

Predicting low oxygen in patients with acute COVID-19 infection isolating at home: a clinical prediction model.

RATIONALE: Identifying patients who could be safely managed at home versus those needing hospitalisation was a particular concern during early COVID-1...

Robust learning framework for a scalable remote monitoring of autonomic dysreflexia: use-case in spinal cord injury.

The autonomous nervous system (ANS) response in neurological disorders is a direct modifiable risk factor for cardiovascular health, however, difficul...

Natriuretic peptides and cardiac troponins in hypertension and heart failure: A contemporary review of the evidence.

Hypertension is the second leading cause of heart failure (HF), yet strategies for identifying hypertensive individuals at increased HF risk remain li...

Machine learning prediction of metabolic-associated fatty liver disease in type 2 diabetes: Emphasizing data imputation and feature selection.

Metabolic-Associated Fatty Liver Disease (MAFLD) is common among Type 2 Diabetes (T2DM) patients. The coexistence of these conditions increases the ri...

Two -stage contrastive learning framework for vertebral compression fracture screening in frontal chest X-ray.

Vertebral Compression Fractures (VCFs) are early signs of osteoporosis and the most common type of osteoporotic fracture. In clinical practice, the pi...

Familial colorectal cancer: risk factors, screening strategies and personalized medicine.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, with approximately 25-30 % of cases exhibiting a familial compo...

Microbiota-host interaction in colorectal cancer: emerging computational technology, multi-omics integration, and mechanisms.

Colorectal cancer (CRC) remains a major global health burden with the gut microbiome emerging as a critical contributor to tumor initiation and progre...

Role of lactic acid-mediated ALKBH5 in depression induced by blue light exposure at night.

Artificial light at night (ALAN) has been classified as a significant environmental endocrine disruptor. Excessive exposure to ALAN has associated wit...