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Erschienen in:
2016 | OriginalPaper | Buchkapitel
IRS-HD: An Intelligent Personalized Recommender System for Heart Disease Patients in a Tele-Health Environment
verfasst von : Raid Lafta, Ji Zhang, Xiaohui Tao, Yan Li, Vincent S. Tseng
Erschienen in: Advanced Data Mining and Applications
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Abstract
The use of intelligent technologies in clinical decision making support may play a promising role in improving the quality of heart disease patients’ life and helping to reduce cost and workload involved in their daily health care in a tele-health environment. The objective of this demo proposal is to demonstrate an intelligent prediction system we developed, called IRS-HD, that accurately advises patients with heart diseases concerning whether they need to take the body test today or not based on the analysis of their medical data during the past a few days. Easy-to-use user friendly interfaces are developed for users to supply necessary inputs to the system and receive recommendations from the system. IRS-HD yields satisfactory recommendation accuracy, offers a promising way for reducing the risk of incorrect recommendations, as well saves the workload for patients to conduct body tests every day.