Parkinson's Disease Diagnosis Using miRNA Biomarkers and Deep Learning.
Front Biosci (Landmark Ed)
; 29(1): 4, 2024 01 12.
Article
em En
| MEDLINE
| ID: mdl-38287819
ABSTRACT
BACKGROUND:
The current standard for Parkinson's disease (PD) diagnosis is often imprecise and expensive. However, the dysregulation patterns of microRNA (miRNA) hold potential as a reliable and effective non-invasive diagnosis of PD.METHODS:
We use data mining to elucidate new miRNA biomarkers and then develop a machine-learning (ML) model to diagnose PD based on these biomarkers.RESULTS:
The best-performing ML model, trained on filtered miRNA dysregulated in PD, was able to identify miRNA biomarkers with 95.65% accuracy. Through analysis of miRNA implicated in PD, thousands of descriptors reliant on gene targets were created that can be used to identify novel biomarkers and strengthen PD diagnosis.CONCLUSIONS:
The developed ML model based on miRNAs and their genomic pathway descriptors achieved high accuracies for the prediction of PD.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Doença de Parkinson
/
MicroRNAs
/
Aprendizado Profundo
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Front Biosci (Landmark Ed)
Ano de publicação:
2024
Tipo de documento:
Article