@inproceedings{fd3ecf8cb1df43789d6635d0ed293779,
title = "A Framework to Recommend Interventions for 30-Day Heart Failure Readmission Risk",
abstract = "In this paper, we describe a novel framework to recommend personalized intervention strategies to minimize 30-day readmission risk for heart failure (HF) patients, as they move through the provider's cardiac care protocol. We design principled solutions by learning the structure and parameters of a multi-layer hierarchical Bayesian network from underlying high-dimensional patient data. Next, we generate and summarize the rules leading to personalized interventions which can be applied to individual patients as they progress from admit to discharge. We present comprehensive experimental results as well as interesting case studies to demonstrate the effectiveness of our proposed framework using large real-world patient datasets on Microsoft Azure for Research platform.",
keywords = "bayesian network, heart failure, intervention recommendation, risk of readmission",
author = "Rui Liu and Kiyana Zolfaghar and Chin, {Si Chi} and Roy, {Senjuti Basu} and Ankur Teredesai",
year = "2014",
month = jan,
day = "1",
doi = "10.1109/ICDM.2014.89",
language = "English (US)",
series = "Proceedings - IEEE International Conference on Data Mining, ICDM",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "January",
pages = "911--916",
editor = "Ravi Kumar and Hannu Toivonen and Jian Pei and {Zhexue Huang}, Joshua and Xindong Wu",
booktitle = "Proceedings - 14th IEEE International Conference on Data Mining, ICDM 2014",
address = "United States",
edition = "January",
note = "14th IEEE International Conference on Data Mining, ICDM 2014 ; Conference date: 14-12-2014 Through 17-12-2014",
}