This paper presents our research work to develop an advanced Self-adaptive Intelligent Monitoring System (SIMS) to help patients, families and clinicians manage chronic conditions associated with heart failure more effectively at home. SIMS takes advantages of a number of advanced technologies from software intelligence, data/knowledge retrieval, data mining and database. SIMS is able to provide a number of advanced functions. It can effectively prioritize patients, provide automatic recommendation for checking frequency and risk assessment, and carry out correlation analysis in order to pinpoint relationships between external factors and the development of patient's heart condition overtime. All these functions can significantly reduce patients' burden for checking, build up their self-confidence of health and enhance their general quality of life. © 2013 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Wang, H., Zhang, J., Soar, J., Tao, X., & Huang, W. (2013). SIMS: Self-adaptive intelligent monitoring system for supporting home-based heart failure patients. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7910 LNCS, pp. 322–330). Springer Verlag. https://doi.org/10.1007/978-3-642-39470-6_43
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