Risk gene identification and support vector machine learning to construct an early diagnosis model of myocardial infarction

The present study aimed to identify genes associated with increased risk of myocardial infarction (MI) and construct an early diagnosis model based on support vector machine (SVM) learning. The gene expression profile data of GSE34198, containing 97 human blood samples including 49 patients with MI...

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Detalles Bibliográficos
Autores principales: Fang, Hong-Zhi, Hu, Dan-Li, Li, Qin, Tu, Su
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2020
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7411293/
https://www.ncbi.nlm.nih.gov/pubmed/32705275
http://dx.doi.org/10.3892/mmr.2020.11247

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7411293/
https://www.ncbi.nlm.nih.gov/pubmed/32705275
http://dx.doi.org/10.3892/mmr.2020.11247

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