Multiple-Disease Risk Predictive Modeling Based on Directed Disease Networks

  • Tingyan Wang
  • Robin G. QiuEmail author
  • Ming Yu
Conference paper
Part of the Springer Proceedings in Business and Economics book series (SPBE)


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.


Directed disease network Predictive modeling Multiple-disease risk assessment 



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).


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Nuffield Department of MedicineUniversity of OxfordOxfordUK
  2. 2.Big Data Lab, Division of Engineering and Information ScienceThe Pennsylvania State UniversityMalvernUSA
  3. 3.Department of Industrial EngineeringHealth Care Services Research Centre, Tsinghua UniversityBeijingChina

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