Back to search

Article

A machine learning model for disease risk prediction by integrating genetic and non-genetic factors

2022-08-23

Abstract excerpt

Polygenic risk score (PRS) has been widely used to identify the high-risk individuals from the general population, which would be helpful for disease prevention and early treatment. Many methods have been developed to calculate PRS by weighted aggregating the phenotype-associated risk alleles from genome-wide association studies. However, only considering genetic effects may not be sufficient for risk prediction b...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
52a88ea4-5230-53d0-9926-4cbd0499e93c
DOI
10.1101/2022.08.22.504882
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
A machine learning model for disease risk prediction by integrating genetic and non-genetic factorsDOI 10.1101/2022.08.22.504882
Select a neighboring publication to make it the new centre.