A Machine Learning Algorithm for Quantitatively Diagnosing Oxidative Stress Risks in Healthy Adult Individuals Based on Health Space Methodology: A Proof-of-Concept Study Using Korean Cross-Sectional Cohort Data

Oxidative stress aggravates the progression of lifestyle-related chronic diseases. However, knowledge and practices that enable quantifying oxidative stress are still lacking. Here, we performed a proof-of-concept study to predict the oxidative stress status in a healthy population using retrospecti...

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Detalles Bibliográficos
Autores principales: Kim, Youjin, Kim, Yunsoo, Hwang, Jiyoung, van den Broek, Tim J., Oh, Bumjo, Kim, Ji Yeon, Wopereis, Suzan, Bouwman, Jildau, Kwon, Oran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8301183/
https://www.ncbi.nlm.nih.gov/pubmed/34356365
http://dx.doi.org/10.3390/antiox10071132

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8301183/
https://www.ncbi.nlm.nih.gov/pubmed/34356365
http://dx.doi.org/10.3390/antiox10071132

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