Latest AI and machine learning research in primary care for healthcare professionals.
AIMS/HYPOTHESIS: Clinically actionable biomarkers that accurately reflect the health status of the beta cell are needed to improve risk stratification and optimise the timing of interventions in type 1 diabetes. We hypothesised that inflammatory stress elicits a reproducible microRNA (miRNA) program in human islets and islet-derived extracellular vesicles (EVs) that can be detected in plasma EVs t...
Cancer remains one of the leading causes of death worldwide and continues to pose a serious public health challenge. The limited success of many current treatments-often due to toxicity, poor selectivity, and the development of drug resistance-highlights the need for new and more effective therapeutic options. Phytochemicals have emerged as a valuable source of anticancer agents, offering rich str...
BACKGROUND: Obesity-induced left ventricular diastolic dysfunction (LVDD), associated with ectopic fat and dysfunctional epicardial adipose tissue (EA...
BACKGROUND: Digital twins (DTs) offer a paradigm for health care by enabling data-driven, simulation-capable representations of individual health traj...
Gastroenterology offers a broad, evidence-based range of preventive measures that goes beyond colorectal cancer screening. As a specialty of systemic ...
OBJECTIVES: To characterize clinical-pathologic tumor features associated with artificial intelligence (AI)-generated risk scores from prior-year scre...
The rapid and accurate detection of multiple cancers presents considerable challenges, especially for stage I disease, due to the low concentration an...
INTRODUCTION: Lymphedema is a chronic complication of breast cancer treatments that can significantly impact the well-being of survivors. This scoping...
OBJECTIVES: To validate blood oxygen level-dependent MRI (BOLD-MRI) for non-invasive discrimination of diabetic nephropathy (DN) vs non-diabetic renal...
BACKGROUND: Effective screening and cohort enrichment remain major challenges in clinical trials for Alzheimer's disease (AD), where traditional diagn...
BACKGROUND: Artificial intelligence (AI) is increasingly recognized for its potential to transform cancer care. However, much of the existing evidence...
BACKGROUND: Predicting mortality among people living with HIV enables clinicians to implement timely, targeted, and preventive interventions at the st...
Active deep learning offers a promising approach for hit discovery starting from limited data by iteratively updating and improving models during scre...
The convergence of artificial intelligence and chemometrics has revolutionized multi-omics data integration, enabling unprecedented insights into comp...
BACKGROUND: Athletes frequently experience potentially traumatic events related to sports injuries, significantly increasing their risk of developing ...
INTRODUCTION: Historically, KRAS mutations have been notoriously difficult to target despite their status as the most commonly mutated oncogene in the...
We present a high-throughput screening approach to identifying safer nonaqueous solvents to replace or modify the flammable, carbonate-based solvents ...
BACKGROUND: Vascular complications of Type 2 diabetes (T2D) significantly contribute to its morbidity and mortality. Identifying robust biomarkers is ...