Comparative effectiveness of medical concept embedding for feature engineering in phenotyping.

Junghwan LeeCong LiuJae Hyun KimAlex ButlerNing ShangChao PangKarthik NatarajanPatrick RyanCasey TaChunhua Weng

Published in: JAMIA open (2021)

MCE enables scalable feature engineering tasks, thereby facilitating phenotyping. Based on current phenotyping practices, MCEs learned by using knowledge graphs constructed by hierarchical relationships among medical concepts outperformed MCEs learned by using EHR data.

Keyphrases

healthcare
high throughput
electronic health record
machine learning
deep learning
primary care
wastewater treatment
working memory
single cell
artificial intelligence