Primary Care

Predicting future dementia from routine clinical MRI and linked healthcare data.

BACKGROUND: Early identification of individuals at risk of dementia is essential for preventive care and timely enrolment into disease-modifying interventions. However, most existing prediction approaches rely on invasive, costly, or research-only biomarkers that are not scalable within public healthcare systems. Routinely acquired National Health Service (NHS) brain magnetic resonance imaging (MR...

The CT colonography radiology and data system: history, updates, and future directions.

Computed tomography colonography, also known as virtual colonoscopy, is a minimally invasive imaging technique developed in the early 1990s to evaluate the colon for polyps, cancer, and other abnormalities. Advances in multidetector computed tomography, bowel preparation protocols, and three-dimensional reconstruction rapidly improved diagnostic performance. Landmark trials demonstrating sensitivi...

Hyperbaric oxygen in the artificial intelligence era: integration and innovation.

Hyperbaric oxygen therapy is established for decompression illness, carbon monoxide poisoning, radiation-induced tissue injury, and diabetic foot ulce...

Proximal Junctional Kyphosis Prevention in Adult Spinal Deformity Surgery: A Technical Review of Tethering and Adjunctive Strategies.

BACKGROUND AND OBJECTIVES: Proximal junctional kyphosis (PJK) and proximal junctional failure (PJF) remain significant complications after long-segmen...

Noninvasive detection and prognostic stratification of biliary tract cancer using cell-free DNA fragmentomics: a model development and validation study.

Biliary tract cancer (BTC) is typically diagnosed at an advanced stage due to the lack of effective screening tools, resulting in limited therapeutic ...

NATURal history of coronary PlaquE on cardiac computed tomography in individuals without MACE or lipid-lowering therapy: NATURE-CTstudy.

BACKGROUND: Coronary artery disease (CAD) progression has been examined mainly in cohorts enriched for major adverse cardiovascular events (MACE), a h...

[Automated analysis of mandibular movements for the screening of obstructive sleep apnea].

INTRODUCTION: Obstructive sleep apnea syndrome (OSAS) is a highly prevalent condition, particularly among at-risk populations such as patients with ob...

Machine learning evaluation of TyG-based metrics for arteriosclerosis progression.

Insulin resistance (IR) is a significant risk factor for arteriosclerosis. The triglyceride-glucose (TyG) index and its obesity-related derivatives (T...

Gender disparities in random blood glucose levels among Pakistani adults with type 2 diabetes: a cross-sectional analysis.

This study investigated gender disparities in random blood glucose (RBS) levels among Pakistani adults with Type 2 Diabetes (T2D), examining biologica...

End-user perspectives on the use of personal health information for AI development and the use of AI in care: an interview study.

INTRODUCTION: The rapid advancement of artificial intelligence (AI) in health care necessitates that decision-makers consider end-user views on second...

Optimization of artificial intelligence models for prediction of new-onset cardiovascular disease in patients with arterial hypertension.

Advanced preventive strategies are needed to decrease the burden of cardiovascular disease (CVD). We aimed to develop a predictive tool to identify in...

Integrated metabolic and inflammatory biomarkers for early association and prediction of adverse pregnancy outcomes: a multicenter validation study.

BACKGROUND: Adverse pregnancy outcomes (APOs) affect long-term maternal and offspring health. Conventional metabolic markers, including the triglyceri...

Predicting intrinsic clearance using deep learning-based drug-metabolic enzyme interaction features on an IVIVE-harmonized endpoint dataset.

BACKGROUND AND OBJECTIVE: Intrinsic clearance is a key pharmacokinetic parameter in drug development because it influences systemic exposure and dose ...

An externally validated machine learning algorithm for predicting mental and physical health outcomes three months post-hospitalization for severe viral infection with SARS-CoV-2.

Many individuals hospitalized due to severe viral infections develop mental and physical sequelae, which could potentially be prevented by targeted in...

Screening and diagnosis of combustion smoking with exhaled breath analysis via proton transfer reaction time-of-flight mass spectrometry.

BACKGROUND: Tobacco smoking is a leading cause for lung cancer, even for non-smokers. Assessing exposure, particularly to passive or secondhand smoke,...

Assessing Extracellular Vesicle Proteins as Predictive Biomarkers for Developing Type 1 Diabetes.

Plasma extracellular vesicles (EVs) are considered excellent sources for biomarker discovery since they carry signatures of their cellular origin and ...

A multi-omics atlas of multisystem complications in type 2 diabetes reveals molecular signatures and improves risk prediction.

BACKGROUND: Type 2 diabetes (T2D) causes multisystem complications, but an integrated multi-omics framework for cross-system, multi-outcome analysis i...

Xiao Zhen Fang mitigates cutaneous toxicity by inhibiting PANoptosis: Insights from untargeted metabolomics and transcriptomics.

BACKGROUND: Epidermal growth factor receptor (EGFR) inhibitors and other targeted therapies frequently cause cutaneous toxicities, impairing patient q...

Enhancing diabetic retinopathy diagnosis and grading: a retrospective study on AI-assisted decision making and cost analysis.

BACKGROUND/AIMS: Diabetic retinopathy (DR) is a major ocular complication of diabetes mellitus. While artificial intelligence (AI)-based DR screening ...

Impact of artificial intelligence on the availability, accessibility, acceptability and quality of ophthalmic disease screening services: a scoping review.

This scoping review examines the existing literature on the application of artificial intelligence (AI) in screening for eye diseases, with a focus on...