TY - GEN
T1 - Multiple-Disease Risk Predictive Modeling Based on Directed Disease Networks
AU - Wang, Tingyan
AU - Qiu, Robin G.
AU - Yu, Ming
N1 - Funding Information:
Acknowledgements A significant part of this work from Tingyan Wang and Robin Qiu was done with the support from the Big Data Lab at Penn State. This project was partially supported by IBM Faculty Awards (RDP-Qiu2016 and RDP-Qiu2017).
Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - This paper studies multiple-disease risk predictive models to assess a discharged patient’s future disease risks. We propose a novel framework that combines directed disease networks and recommendation system techniques to substantially enhance the performance of multiple-disease risk predictive modeling. Firstly, a directed disease network considering patients’ temporal information is developed. Then based on this directed disease network, we investigate different disease risk score computing approaches. We validate the proposed approaches using a hospital’s dataset. Promisingly, the predictive results can be well referenced by healthcare professionals who provide healthcare guidance for patients ready for discharge.
AB - This paper studies multiple-disease risk predictive models to assess a discharged patient’s future disease risks. We propose a novel framework that combines directed disease networks and recommendation system techniques to substantially enhance the performance of multiple-disease risk predictive modeling. Firstly, a directed disease network considering patients’ temporal information is developed. Then based on this directed disease network, we investigate different disease risk score computing approaches. We validate the proposed approaches using a hospital’s dataset. Promisingly, the predictive results can be well referenced by healthcare professionals who provide healthcare guidance for patients ready for discharge.
UR - https://www.scopus.com/pages/publications/85126139908
UR - https://www.scopus.com/pages/publications/85126139908#tab=citedBy
U2 - 10.1007/978-3-030-30967-1_21
DO - 10.1007/978-3-030-30967-1_21
M3 - Conference contribution
AN - SCOPUS:85126139908
SN - 9783030309664
T3 - Springer Proceedings in Business and Economics
SP - 229
EP - 240
BT - Smart Service Systems, Operations Management, and Analytics - Proceedings of the 2019 INFORMS International Conference on Service Science
A2 - Yang, Hui
A2 - Qiu, Robin
A2 - Chen, Weiwei
PB - Springer Science and Business Media B.V.
T2 - INFORMS International Conference on Service Science, INFORMS-CSS 2019
Y2 - 27 June 2019 through 29 June 2019
ER -