Polygenic risk scores (PRSs) are an emerging tool to predict the clinical phenotypes and
outcomes of individuals. We propose PRSmix, a framework that leverages the PRS corpus …

Many clinical tasks require an understanding of specialized data, such as medical images
and genomics, which is not typically found in general-purpose large multimodal models …

Abstract Purpose of Review Coronary artery disease (CAD) is a common and etiologically
complex disease worldwide. Current guidelines for primary prevention, or the prevention of …

Accurate polygenic scores (PGSs) facilitate the genetic prediction of complex traits and aid
in the development of personalized medicine. Here, we develop a statistical method called …

Polygenic risk scores (PRSs) are now showing promising predictive performance on a wide
variety of complex traits and diseases, but there exists a substantial performance gap across …

In the past two decades, significant progress has been made in the development of
polygenic scores (PGSs). One specific application of PGSs is the development and potential …

Polygenic risk scores (PRSs) are expected to play a critical role in precision medicine.
Currently, PRS predictors are generally based on linear models using summary statistics …

Background Antimicrobial resistance (AMR) poses a significant global health threat, and an
accurate prediction of bacterial resistance patterns is critical for effective treatment and …

We introduce an innovative statistical framework to optimize and benchmark polygenic risk
score (PRS) models using summary statistics of genome-wide association studies. This …

Background and Objective: Hypertension increases the risk of cardiovascular diseases
(CVD) such as stroke, heart attack, heart failure, and kidney disease, contributing to global …