Primary Care

Precision forensic toxicology: Leveraging Toxicogenomics, multi-omics, and artificial intelligence for next-generation poisoning investigations.

For much of its history, forensic toxicology was built on a core analytical question: what poison or drug is present, and at what concentration? That question still matters, but modern casework increasingly shows that it is no longer sufficient on its own. The field grew from the nineteenth-century chemical toxicology of Mathieu Orfila and the arsenic-detecting Marsh test into a discipline central...

From Structure to Selectivity: Integrating CADD and AIDD in Rational Medicinal Chemistry Strategies for DYRK1A Inhibitor Discovery.

Dual specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A), a member of the CMGC kinase family, regulates diverse cellular processes and is implicated in Alzheimer's disease, Down syndrome, cancer, and diabetes. However, the clinical translation of DYRK1A inhibitors remains challenging due to limited selectivity arising from the high structural conservation of the ATP-binding pocket wi...

A comprehensive evaluation of seven osteoporosis screening tools.

UNLABELLED: This review evaluates the sensitivity, specificity, and predictive values of seven osteoporosis screening tools in populations such as pos...

Bioinformatics, Machine Learning and Functional Validation Reveal Mitophagy-Related FABP5 and HMOX1 as Diagnostic and Therapeutic Targets in Polycystic Ovary Syndrome.

Polycystic Ovary Syndrome (PCOS) is a heterogeneous endocrine-metabolic disorder characterized by ovulatory dysfunction, hyperandrogenism, and insulin...

Explainable machine learning model for early prediction of ICU death in chronic heart failure with pulmonary infection.

OBJECTIVE: To develop and validate a machine learning model for predicting ICU mortality in CHF patients with pulmonary infection. METHODS: Clinical d...

Artificial intelligence for pediatric rare disease diagnosis: a multimethod study integrating published evidence and clinician interviews.

BACKGROUND: Pediatric rare diseases are highly heterogeneous and are frequently associated with missed or delayed diagnosis, creating substantial burd...

Development and temporal validation of a machine-learning based risk prediction model for depression in older adults with chewing difficulty: evidence from the KNHANES.

BACKGROUND: Depression in older adults is a multifactorial condition influenced by demographic, behavioral, and health-related factors. Oral functiona...

A feature-efficient dual-task machine learning framework for predicting bone mineral density and osteoporosis stratification in resource-constrained environments.

Osteoporosis is a chronic skeletal disorder characterized by progressive bone mineral density (BMD) loss and structural deterioration, significantly i...

RT2C: Predicting Time-to-New Caries with Structured Dental Data Using RNN.

Dental caries is a highly prevalent chronic condition requiring accurate tools to identify at-risk patients and guide preventive care. Most existing c...

Age-Related Brain Atrophy Mediates a Composite Outcome of One-Year Ischemic Stroke Recurrence and All-Cause Mortality Through YKL-40-Related Inflammatory Pathways: A Structural Equation Model.

Chronological age is a strong predictor of poor outcomes after ischemic stroke but may not fully capture underlying biological vulnerability. This stu...

Predictive Modeling of Coronary Artery Disease Using Color Fundus Photography-Based Features of Retinal Vasculature.

INTRODUCTION: Coronary artery disease (CAD) remains the leading cause of death and current screening methods are limited. Color fundus photography (CF...

The Role and Impact of Artificial Intelligence in Preventive Dentistry: A Scoping Review.

OBJECTIVE: This scoping review aims to identify the current applications of artificial intelligence (AI) in preventive dentistry for primary disease p...

Association of Histological Features of Cortical and Medullary Peritubular Capillaries With Progressive CKD.

RATIONALE & OBJECTIVE: Peritubular capillary (PTC) rarefaction occurs in chronic kidney disease (CKD), but the independent association of PTC histolog...

Exploratory development of prediction models for pharmacotherapy outcomes in trigeminal neuralgia: a combined analysis based on multi-source data.

BACKGROUND: Drug-refractory trigeminal neuralgia (DRTN) represents a formidable challenge in clinical management, with approximately 30%-50% of patien...

A combi-elasto ultrasound based deep learning model on liver fibrosis staging for suspected MASLD/MASH patients.

OBJECTIVES: Metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH) weakened the ...

Enhancing virtual screening of cystathionine β-synthase inhibitors: benchmarking target-specific machine-learning scoring functions against state-of-the-art AI docking and co-folding approaches.

Cystathionine β-synthase (CBS) has emerged as an important therapeutic target implicated in cancer and Down syndrome, yet the discovery of selective C...

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 ...

The Science of Preventing Delirium: Trends, Knowledge Gaps, and Future Directions Revealed Through Bibliometric Insights.

PURPOSE: To examine global research trends in delirium prevention through a bibliometric analysis and provide a structured overview of its development...

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 a...

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) ...