New article titled "Machine learning for effectively avoiding overfitting is a crucial strategy for the genetic prediction of polygenic psychiatric phenotypes" was published on the journal of Translational Psychiatry. Please take a look at the article for more details.  

Fig. 1: The concept of genetic architecture and predictive models for polygenic diseases.

Article information

Title: Machine learning for effectively avoiding overfitting is a crucial strategy for the genetic prediction of polygenic psychiatric phenotypes
Published journal: Translational Psychiatry
Authors:Yuta Takahashi, Masao Ueki, Gen Tamiya, Soichi Ogishima, Kengo Kinoshita, Atsushi Hozawa, Naoko Minegishi, Fuji Nagami, Kentaro Fukumoto, Kotaro Otsuka, Kozo Tanno, Kiyomi Sakata, Atsushi Shimizu, Makoto Sasaki, Kenji Sobue, Shigeo Kure, Masayuki Yamamoto, Hiroaki Tomita
Publish date: 17 Aug 2020
doi:10.1038/s41398-020-00957-5

Related Link

New article about improved metabolomic data-based prediction of depressive symptoms using nonlinear machine learning with feature selection was published