Preventive Care

Risk Factors for Cardiovascular Disease: Epidemiology, Screening, Prevention, and Therapeutic Interventions.

Cardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality worldwide, and the burden is particularly severe in low-income and middle-income countries. Although traditional risk factors such as hypertension, dyslipidemia, diabetes, and smoking have been well established, new research evidence indicates that inflammation, environmental exposure, psychological and social stres...

Low vitamin D status and cardiometabolic trait clustering in a primary-care adult cohort: association analysis and exploratory explainable machine-learning classification.

BACKGROUND: Low serum 25-hydroxyvitamin D (25(OH)D) commonly co-exists with obesity and adverse cardiometabolic traits. However, its cross-sectional association with dyslipidaemia, body composition and glycaemic markers in primary-care adults remains incompletely characterised. This study examined these associations as the primary objective and, as a secondary exploratory objective, assessed wheth...

Artificial Intelligence Across the Vaccine Clinical Trial Lifecycle: Evidence, Readiness, and Guardrails.

Artificial intelligence (AI) is increasingly being used to support clinical research, but its value in vaccine clinical trials requires careful eviden...

An interpretable machine learning model integrating ultrasound and clinical variables for predicting osteoporosis in patients with rheumatoid arthritis.

OBJECTIVES: Rheumatoid arthritis (RA) significantly increases the risk of osteoporosis (OP) and fractures, yet dual-energy X-ray absorptiometry (DXA) ...

Development and external validation of AI-ECG models in athlete pre-participation screening: Performance, limitations, and clinical implications.

BACKGROUND: Pre-participation screening (PPS) in competitive athletes aims to identify cardiovascular diseases associated with sudden cardiac death (S...

Clinical applications of artificial intelligence in hypertension management: current evidence and future perspectives.

BACKGROUND: Hypertension remains the leading modifiable risk factor for cardiovascular morbidity and mortality worldwide, with persistently inadequate...

Human salivary microbiome as a potential non-invasive biomarker for early-onset colorectal cancer screening: a prospective study.

BACKGROUND: The incidence of early-onset colorectal cancer (EOCRC) has been increasing in recent years, the carcinogenesis of which has been linked to...

The VISION-AI Trial: protocol for a pragmatic randomized controlled non-inferiority trial comparing artificial intelligence-guided colonoscopy to pancolonic chromoendoscopy for neoplasia detection in adults with colorectal inflammatory bowel disease.

BACKGROUND: Current guidelines recommend pancolonic chromoendoscopy (pCE) over white light endoscopy (WLE) alone for colorectal neoplasia (CRN) detect...

Techniques, Performance, and Feasibility of Natural Language Processing for Abstract Screening in Evidence Synthesis: A Systematic Review.

BACKGROUND: Natural language processing (NLP) techniques offer promising solutions for semi-automating the time-consuming process of abstract screenin...

Strategies to overcome barriers in access to cancer treatment in Latin America: a regional perspective.

Access to high-quality cancer care remains a major challenge across Latin America, particularly for patients with gastrointestinal (GI) malignancies. ...

A Guideline-Concordant Chatbot Framework for Structured Colorectal Cancer Screening: Multistage Feasibility Study.

BACKGROUND: Colorectal cancer (CRC) screening relies on structured risk assessment and guideline-concordant communication, which remain challenging to...

Cancer Vaccine Development: Toward Artificial Intelligence-Assisted Personalized Cell Membrane Nanovaccine.

Cancer vaccines are an attractive immunotherapeutic approach, and numerous clinical trials are ongoing. However, most candidates have not achieved sta...

Development and internal validation of an interpretable machine learning model using routine laboratory data for systemic sclerosis-associated pulmonary arterial hypertension.

This study aimed to develop and validate an interpretable machine learning (ML) model using routine laboratory data to support clinical decision-makin...

Artificial intelligence-assisted detection and optical differentiation of colorectal lesions in Lynch syndrome surveillance (CADLY2): a multicentre, open-label, randomised controlled superiority trial.

BACKGROUND: Artificial intelligence (AI)-based computer-aided detection (CADe) systems improve adenoma detection in average-risk colorectal cancer scr...

Human-artificial intelligence adaptation in colonoscopy: beyond deskilling and upskilling.

BASG-Net: a background-aware spatial gating network for cervical cell segmentation in pap smear images.

The precise segmentation of cervical cell images is regarded as a fundamental prerequisite for the implementation of computer-aided cervical cancer sc...

An efficient framework for real-time colorectal polyp detection using local outlier factor-based preprocessing and YOLOv11n.

Timely and accurate detection of colorectal polyps plays an important role in the prevention and early diagnosis of colorectal cancer. Despite the adv...

BiCervi: Pap smear microscopy image dataset for cervical cancer detection and classification.

Cervical cancer is still a major public-health challenge, especially in low and middle-income countries where there are limited numbers of specialists...

Application of AI in Hypertension Health Education: Scoping Review.

BACKGROUND: Hypertension is a major global health challenge, and effective health education is crucial for improving patients' self-management. Tradit...

Passive Screening for Depressive Symptoms Using Daily Wrist Actigraphy and Deep Learning: Model Development and Validation Study.

BACKGROUND: Depressive symptoms are common yet often underrecognized in routine care, underscoring the need for scalable screening approaches beyond e...