Yanfei Zhang

TL;DR: This article is a review of applications for machine learning in health care with a focus on clinical, translational, and public health applications with an overview of the important role of privacy, data sharing, and genetic information.

TL;DR: In this paper, associations of restricted and genome-wide polygenic risk scores (PRSs) with coronary heart disease (CHD) in three major racial and ethnic groups in the U.S. were investigated.

TL;DR: In this paper, a pooled analysis of data from newly recruited patients with an MRI-confirmed diagnosis of lacunar stroke and existing genome-wide association studies (GWAS) was performed to identify novel associations and provide mechanistic insights into the disease.

TL;DR: The network approach applied in this study can be used to uncover interactions between diseases as a result of their shared, potentially pleiotropic SNPs, and advance clinical research and even clinical practice by accelerating the understanding of disease mechanisms on the basis of similar underlying genetic associations.

TL;DR: The authors' data suggested the changes in DNA methylation occurred at the late stage of OA, which highlighted potential etiologic mechanism and implicated the potential cartilage regeneration in theLate stage of knee OA.