Random forest model for feature-based Alzheimer's disease conversion prediction from early mild cognitive impairment subjects.
Alzheimer's Disease (AD) conversion prediction from the mild cognitive impairment (MCI) stage has been a difficult challenge. This study focuses on providing an individualized MCI to AD conversion prediction using a balanced random forest model that leverages clinical data. In order to do this,...
| Autores principales: | , , |
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| Formato: | Artículo |
| Lenguaje: | English |
| Publicado: |
Public Library of Science (PLoS)
2021-01-01
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| Colección: | PLoS ONE |
| Acceso en línea: | https://doi.org/10.1371/journal.pone.0244773 |