Multi-omics and immune cells' profiling of COVID-19 patients for ICU admission prediction: in silico analysis and an integrated machine learning-based approach in the framework of Predictive, Preventive, and Personalized Medicine.

"within the geo (gene expression omnibus) dataset (gse157103) we identified 26 noncovid-19 and 100 covid-19 patients with available transcriptome expression matrix demographic and clinical baseline data."

"Declarations Ethics approvalNot applicable. Consent to participateNot applicable. Consent for publicationAll authors gave their consent for publication. Competing interestsThe authors declare no competing interests. Competing interests The authors declare no competing interests."

"Funding This research was supported by the following funds: Zhejiang University special scientific research fund for COVID-19 prevention and control, (Q.S.); National Natural Science Foundation of China, 82272191 (Q.S.); National Natural Science Foundation of China, 81901989 (D.L.); Natural Science Foundation of Zhejiang Province, LY21H150005 (D.L.); Foundation for The Top-Notch Youth Talent Cultivation Project of Independent Design Project of National Clinical Research Center for Child Health, Q21B0007 (D.L.); Special Fund for the Incubation of Young Clinical Scientist, The Children’s Hospital of Zhejiang University School of Medicine, CHZJU2022YS002 (D.L.)."