Evaluation of penalized and machine learning methods for asthma disease prediction in the Korean Genome and Epidemiology Study (KoGES)

Abstract Background Genome-wide association studies have successfully identified genetic variants associated with human disease. Various statistical approaches based on penalized and machine learning methods have recently been proposed for disease prediction. In this study, we evaluated the performa...

Full beskrivning

Bibliografiska uppgifter

Huvudupphov:	Yongjun Choi, Junho Cha, Sungkyoung Choi
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	BMC 2024-02-01
Serie:	BMC Bioinformatics
Ämnen:	Disease risk prediction model Large-scale genetic data Asthma Penalized methods Machine learning methods Ensemble methods
Länkar:	https://doi.org/10.1186/s12859-024-05677-x
Taggar:	Lägg till en tagg Inga taggar, Lägg till första taggen!