An intelligent recommender system based on predictive analysis in telehealthcare environment

Raid Lafta, Ji Zhang, Xiaohui Tao, Yan Li, Vincent S. Tseng, Yonglong Luo, Fulong Chen
  • Web Intelligence, November 2016, IOS Press
  • DOI: 10.3233/web-160348

An intelligent recommender system based on predictive analysis in telehealthcare environment

What is it about?

This paper is offering an intelligent recommender system, supported by several innovative predictive algorithms, for short-term risk assessment on patients in telehealth environment based on analytic of a patient's historical medical data.

Why is it important?

The system provides recommendations to patients such as heart diseases patients in relation to the necessity of medical tests taken on a daily basis. The research is conducted with an aim at improving the quality of clinical evidenced-based decisions made by medical practitioners to help reduce the financial and timing cost taken by patients.


Raid Lafta

The proposed system yields reasonably good recommendation accuracy and can effectively reduce the workload required in medical tests for the patients. We believe that this system is promising in risk assessment and management associated with heart failure and other similar diseases.

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The following have contributed to this page: Raid Lafta and Fulong Chen

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