@inproceedings{068a18ac33554777a7695c95099cbc99,
title = "Patient ADE Risk Prediction through Hierarchical Time-Aware Neural Network Using Claim Codes",
abstract = "Adverse drug events (ADEs) are a serious health problem that can be life-threatening. While a lot of work on detecting correlation between a drug and an ADE, limited studies have been conducted on personalized ADE risk prediction. Avoiding the drugs with high likelihood of causing severe ADEs helps physicians to provide safer treatments to patients. The goal of this study is to assess personalized ADE risks that a target drug may induce on a target patient, based on patient medical history recorded in claim codes, which provide information about diagnosis, drugs taken, related medical supplies besides billing information. We developed a HTNNR model (Hierarchical Time-aware Neural Network for ADE Risk) that captures characteristics of claim codes and their relationship. Eempirical evaluation shows that the proposed HTNNR model substantially outperforms the comparison methods.",
keywords = "Adverse Drug Events, Claim Codes, Neural Networks, Personalized Risk Assessment",
author = "Jinhe Shi and Xiangyu Gao and Chenyu Ha and Yage Wang and Guodong Gao and Yi Chen",
note = "Funding Information: The work is partially supported by the Leir Foundation, a grant from the National Institutes of Health (UL1TR003017), a Google Faculty Research Award, and a Faculty Seed Grant from the Henry J. and Erna D. Leir Research Institute for Business, Technology, and Society at NJIT. Publisher Copyright: {\textcopyright} 2020 IEEE.; 8th IEEE International Conference on Big Data, Big Data 2020 ; Conference date: 10-12-2020 Through 13-12-2020",
year = "2020",
month = dec,
day = "10",
doi = "10.1109/BigData50022.2020.9378336",
language = "English (US)",
series = "Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1388--1393",
editor = "Xintao Wu and Chris Jermaine and Li Xiong and Hu, {Xiaohua Tony} and Olivera Kotevska and Siyuan Lu and Weijia Xu and Srinivas Aluru and Chengxiang Zhai and Eyhab Al-Masri and Zhiyuan Chen and Jeff Saltz",
booktitle = "Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020",
address = "United States",
}