@inproceedings{a3c833a103f04aec85627482bc603392,
title = "Early Prediction of Acute Kidney Injury in Critical Care Setting Using Clinical Notes",
abstract = "Acute kidney injury (AKI) in critically ill patients is associated with significant morbidity and mortality. Development of novel methods to identify patients with AKI earlier will allow for testing of novel strategies to prevent or reduce the complications of AKI. We developed data-driven prediction models to estimate the risk of new AKI onset. We generated models from clinical notes within the first 24 hours following intensive care unit (ICU) admission extracted from Medical Information Mart for Intensive Care III (MIMIC-III). From the clinical notes, we generated clinically meaningful word and concept representations and embeddings, respectively. Five supervised learning classifiers and knowledge-guided deep learning architecture were used to construct prediction models. The best configuration yielded a competitive AUC of 0.779. Our work suggests that natural language processing of clinical notes can be applied to assist clinicians in identifying the risk of incident AKI onset in critically ill patients upon admission to the ICU.",
keywords = "Machine Learning, Medical Decision Making, Natural Language Processing, Unified Medical Language System",
author = "Yikuan Li and Liang Yao and Chengsheng Mao and Anand Srivastava and Xiaoqian Jiang and Yuan Luo",
note = "Funding Information: This work was supported in part by NIH Grant 1R21LM012618. Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 ; Conference date: 03-12-2018 Through 06-12-2018",
year = "2019",
month = jan,
day = "21",
doi = "10.1109/BIBM.2018.8621574",
language = "English (US)",
series = "Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "683--686",
editor = "Harald Schmidt and David Griol and Haiying Wang and Jan Baumbach and Huiru Zheng and Zoraida Callejas and Xiaohua Hu and Julie Dickerson and Le Zhang",
booktitle = "Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018",
address = "United States",
}