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A large-scale UK Biobank study demonstrates that combining NMR metabolomics, polygenic risk scores, and clinical biomarkers with SCORE2 significantly enhances cardiovascular risk prediction, potentially doubling the number of prevented even
This review evaluates the impact of integrating risk-prediction models into shared decision-making for lung cancer screening, focusing on clinical implementation strategies that prioritize high-benefit populations.
This review evaluates AI algorithms predicting heart failure risk from noisy single-lead ECGs, synthesizing evidence from large multinational cohorts, highlighting improved risk stratification with AI-ECG models beyond traditional clinical
A novel risk prediction model for 10-year heart failure or cardiomyopathy offers tailored cardiac management strategies for women undergoing breast cancer therapy.
This study demonstrates that the triglyceride glucose-waist height ratio (TyG-WHtR) index independently predicts cardiometabolic multimorbidity risk in Chinese adults aged ≥45, showing a linear dose-response relationship and improved predic
This study demonstrates that insulin resistance indices, particularly TyG-WC, TyG-WHtR, and METS-IR, robustly predict the risk and progression of cardio-renal-metabolic multimorbidity, with inflammation and kidney function mediating these a
Machine learning models trained on clinical data improve prediction of coronary artery disease on CT scans compared to traditional risk scores, potentially guiding better resource utilization in cardiovascular care.
AI-enhanced ECG models, initially designed for specific cardiac diagnoses, reveal broader cardiovascular risk detection and prediction capabilities, challenging their use as condition-specific tools and supporting their role as comprehensiv
Coronary CTA, guided by clinical risk models and advanced radiomic plaque analysis, improves prediction and prevention of myocardial infarction in patients with new-onset chest pain, particularly in those with low clinical likelihood of cor
