A Machine Learning Approach to Parkinson’s Disease Blood Transcriptomics

A Machine Learning Approach to Parkinson’s Disease Blood Transcriptomics

The increased incidence and the significant health burden associated with Parkinson’s disease (PD) have stimulated substantial research efforts towards the identification of effective treatments and diagnostic procedures. Despite technological advancements, a cure is still not available and PD is of...

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Bibliographic Details
Main Authors: Amoroso, N. (Author), Bellantuono, L. (Author), Bellotti, R. (Author), Giudice, C.L (Author), Logroscino, G. (Author), Lombardi, A. (Author), Monaco, A. (Author), Nigro, S. (Author), Pantaleo, E. (Author), Pesole, G. (Author), Picardi, E. (Author), Tafuri, B. (Author), Tangaro, S. (Author), Urso, D. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
blood transcriptomics
feature selection
inflammation
machine learning
mitochondrial dysfunction
oxidative stress
Parkinson’s disease
xgboost
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