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

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

Abstract 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...

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Bibliographic Details
Main Authors: Jie Xu, Fei Wang, Zhenxing Xu, Prakash Adekkanattu, Pascal Brandt, Guoqian Jiang, Richard C. Kiefer, Yuan Luo, Chengsheng Mao, Jennifer A. Pacheco, Luke V. Rasmussen, Yiye Zhang, Richard Isaacson, Jyotishman Pathak
Format: Article
Language:English
Published: Wiley 2020-10-01
Series:Learning Health Systems
Subjects:
Alzheimer's disease
electronic health records
subphenotypes
Online Access:https://doi.org/10.1002/lrh2.10246

Internet

https://doi.org/10.1002/lrh2.10246

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