@inproceedings{1d6c00c144b94145b142f2d9048ac1b4,
title = "An Anytime Querying Algorithm for Predicting Cardiac Arrest in Children: Work-in-Progress",
abstract = "Cardiac arrest (CA) is a devastating complication for children in the cardiac intensive care unit (CICU). We developed an “anytime{"} algorithm to predict CA, using the first few hours of EHR data for initial approximation, and then using information from subsequent time periods to augment the predictive model, improving performance at each iteration. Our initial empirical evaluation on EHR CICU data shows that the model achieves significantly higher performance than learning with all the available data at each iteration when predicting CA inside CICU.",
keywords = "Anytime algorithms, Cardiac arrest, Gradient boosting",
author = "Skinner, {Michael A.} and Priscilla Yu and Lakshmi Raman and Sriraam Natarajan",
note = "Funding Information: S. Natarajan—Supported in part by NICHD grant 1R01HD101246 and The Precision Health Initiative of Indiana University. Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 20th International Conference on Artificial Intelligence in Medicine, AIME 2022 ; Conference date: 14-06-2022 Through 17-06-2022",
year = "2022",
doi = "10.1007/978-3-031-09342-5_34",
language = "English (US)",
isbn = "9783031093418",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "353--357",
editor = "Martin Michalowski and Abidi, {Syed Sibte Raza} and Samina Abidi",
booktitle = "Artificial Intelligence in Medicine - 20th International Conference on Artificial Intelligence in Medicine, AIME 2022, Proceedings",
address = "Germany",
}