Predicting future amyloid biomarkers in dementia patients with machine learning to improve clinical trial patient selection

INTRODUCTION: In Alzheimer's disease, asymptomatic patients may have amyloid deposition, but predicting their progression rate remains a substantial challenge with implications for clinical trial enrollment. Here, we demonstrate an artificial intelligence approach to use baseline clinical infor...

Descripción completa

Detalles Bibliográficos
Autores principales: Reith, Fabian H., Mormino, Elizabeth C., Zaharchuk, Greg
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8515556/
https://www.ncbi.nlm.nih.gov/pubmed/34692985
http://dx.doi.org/10.1002/trc2.12212

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8515556/
https://www.ncbi.nlm.nih.gov/pubmed/34692985
http://dx.doi.org/10.1002/trc2.12212

Ejemplares similares