Data‐driven discovery of probable Alzheimer's disease and related dementia subphenotypes using electronic health records

INTRODUCTION: We sought to assess longitudinal electronic health records (EHRs) using machine learning (ML) methods to computationally derive probable Alzheimer's Disease (AD) and related dementia subphenotypes. METHODS: A retrospective analysis of EHR data from a cohort of 7587 patients seen a...

Descripción completa

Detalles Bibliográficos
Autores principales: Xu, Jie, Wang, Fei, Xu, Zhenxing, Adekkanattu, Prakash, Brandt, Pascal, Jiang, Guoqian, Kiefer, Richard C., Luo, Yuan, Mao, Chengsheng, Pacheco, Jennifer A., Rasmussen, Luke V., Zhang, Yiye, Isaacson, Richard, Pathak, Jyotishman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Research Reports
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7556420/
https://www.ncbi.nlm.nih.gov/pubmed/33083543
http://dx.doi.org/10.1002/lrh2.10246

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7556420/
https://www.ncbi.nlm.nih.gov/pubmed/33083543
http://dx.doi.org/10.1002/lrh2.10246

Ejemplares similares