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Article

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

Molecular medicine reports - 1 Sept 2020

Fang Hong-Zhi, Hu Dan-Li, Li Qin, Tu Su

Abstract excerpt

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 and 48 healthy individuals, were obtained from the Gene Expression Omnibus database. Differentially expressed...

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Source

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Identifiers

PMID: 32705275
DOI: 10.3892/mmr.2020.11247
PMCID: PMC7411293

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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