Develop and validate a computable phenotype for the identification of Alzheimer's disease patients using electronic health record data.

Xing HeRuoqi WeiYu HuangZhaoyi ChenTianchen LyuSarah BostJiayi TongLu LiYujia ZhouZhao LiJingchuan GuoHuilin TangFei WangSteven DeKoskyHua XuYong ChenRui ZhangJie XuYi GuoYonghui WuJiang Bian

Published in: Alzheimer's & dementia (Amsterdam, Netherlands) (2024)

Developed a computable phenotype (CP) to identify Alzheimer's disease (AD) patients using EHR data.Utilized both structured and unstructured EHR data to enhance CP accuracy.Achieved a high F1-score of 0.817 at UFHealth, and 0.961 and 0.623 at UTHealth and UMN.Validated the CP across different demographics, ensuring robustness and fairness.

Keyphrases

electronic health record
end stage renal disease
ejection fraction
newly diagnosed
chronic kidney disease
clinical decision support
peritoneal dialysis
prognostic factors
big data
cognitive decline
adverse drug
patient reported outcomes
bioinformatics analysis