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Article

Machine learning approach to single nucleotide polymorphism-based asthma prediction.

PloS one - 1 Jan 2019

Gaudillo Joverlyn, Rodriguez Jae Joseph Russell, Nazareno Allen, Baltazar Lei Rigi, Vilela Julianne, Bulalacao Rommel, Domingo Mario, Albia Jason

Abstract excerpt

Machine learning (ML) is poised as a transformational approach uniquely positioned to discover the hidden biological interactions for better prediction and diagnosis of complex diseases. In this work, we integrated ML-based models for feature selection and classification to quantify the risk of individual susceptibility to asthma using single nucleotide polymorphism (SNP). Random forest (RF) and recursive feature...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 31800601
DOI: 10.1371/journal.pone.0225574
PMCID: PMC6892549

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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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