Kenney Ng

The paper uses machine learning to analyze myocardial T1 time in UK Biobank data, identifying genetic loci and pathways associated with interstitial fibrosis and related cardiovascular diseases.

The paper uses deep learning and genome-wide association studies to identify genetic loci associated with right heart structure and function in 40,000 individuals.

This paper develops a cross-modal autoencoder framework to integrate cardiac MRI and ECG data, improving phenotype prediction and enabling MRI imputation from ECGs.

The paper designs and tests a polygenic score report for coronary artery disease, identifying user preferences for visual elements, risk communication, and personalized resources.

This study constructs a disease network from EHR data to map cardiovascular disease progression and identifies age-associated progression paths and risk models.

The paper examines how polygenic risk modifies the penetrance of monogenic variants in coronary artery disease, breast cancer, and colorectal cancer across multiple cohorts.