Cargando…
Identification of Transcriptome Biomarkers for Severe COVID-19 with Machine Learning Methods
The rapid spread of COVID-19 has become a major concern for people’s lives and health all around the world. COVID-19 patients in various phases and severity require individualized treatment given that different patients may develop different symptoms. We employed machine learning methods to discover...
Autores principales: | Li, Xiaohong, Zhou, Xianchao, Ding, Shijian, Chen, Lei, Feng, Kaiyan, Li, Hao, Huang, Tao, Cai, Yu-Dong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9775121/ https://www.ncbi.nlm.nih.gov/pubmed/36551164 http://dx.doi.org/10.3390/biom12121735 |
Ejemplares similares
-
Predicting Heart Cell Types by Using Transcriptome Profiles and a Machine Learning Method
por: Ding, Shijian, et al.
Publicado: (2022) -
Identifying COVID-19-Specific Transcriptomic Biomarkers with Machine Learning Methods
por: Chen, Lei, et al.
Publicado: (2021) -
Identifying Methylation Signatures and Rules for COVID-19 With Machine Learning Methods
por: Li, Zhandong, et al.
Publicado: (2022) -
Identification of methylation signatures and rules for predicting the severity of SARS-CoV-2 infection with machine learning methods
por: Liu, Zhiyang, et al.
Publicado: (2022) -
Identification of Methylation Signatures and Rules for Sarcoma Subtypes by Machine Learning Methods
por: Ren, Jingxin, et al.
Publicado: (2022)