Forecasting the progression of Alzheimer's disease using neural networks and a novel preprocessing algorithm

INTRODUCTION: There is a 99.6% failure rate of clinical trials for drugs to treat Alzheimer's disease, likely because Alzheimer's disease (AD) patients cannot be easily identified at early stages. This study investigated machine learning approaches to use clinical data to predict the progr...

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Detalles Bibliográficos
Autor principal: Albright, Jack
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6804703/
https://www.ncbi.nlm.nih.gov/pubmed/31650004
http://dx.doi.org/10.1016/j.trci.2019.07.001

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6804703/
https://www.ncbi.nlm.nih.gov/pubmed/31650004
http://dx.doi.org/10.1016/j.trci.2019.07.001

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