Adaptive best subset selection algorithm and genetic algorithm aided ensemble learning method identified a robust severity score of COVID-19 patients.

Kong, Weikaixin; Zhu, Jie; Bi, Suzhen; Huang, Liting; Wu, Peng; Zhu, Su-Jie

Kong, Weikaixin; Zhu, Jie; Bi, Suzhen; Huang, Liting; Wu, Peng; Zhu, Su-Jie.

Affiliation

Kong W; Institute for Molecular Medicine Finland (FIMM), HiLIFE University of Helsinki Helsinki Finland.
Zhu J; Institute for Molecular Medicine Finland (FIMM), HiLIFE University of Helsinki Helsinki Finland.
Bi S; Institute of Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine Qingdao University Qingdao China.
Huang L; Institute of Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine Qingdao University Qingdao China.
Wu P; Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital Huazhong University of Science and Technology Wuhan China.
Zhu SJ; Department of Gynecologic Oncology, Tongji Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China.

Imeta ; 2(3): e126, 2023 Aug.

Article de En | MEDLINE | ID: mdl-38867930

ABSTRACT

ABSTRACT

We used an integrated ensemble learning method to build a stable prediction model for severity in COVID-19 patients, which was validated in multicenter cohorts.

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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Langue: En Journal: Imeta Année: 2023 Type de document: Article Pays de publication: Australie

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