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About 50% of the patients diagnosed with heart failure die within four years. At the same time, a rise in home telemonitoring of these patients can be observed. For its successful deployment, predicting if a heart failure patient could die within a certain period of time is an important task. An investigation of an alternating decision tree employed for(More)
A leading cause of hospital admission in the elderly is heart failure and it is considered a major financial burden since the hospitalization costs are high. This is intensified with a lack of medical professionals due to a continuing significant increase of patients with heart failure as a result of obesity, diabetes and aging population. Integration of an(More)
Medical decision support is one area of increasing research interest. Ongoing collaborations between cardiovascular clinicians and computer scientists are looking at the application of data mining techniques to the area of individual patient diagnosis, based on clinical records. An investigation of four different classification models on cardiovascular data(More)
Cardiovascular decision support is one area of increasing research interest. On-going collaborations between clinicians and computer scientists are looking at the application of knowledge discovery in databases to the area of patient diagnosis, based on clinical records. A fuzzy rule-based system for risk estimation of cardiovascular patients is proposed.(More)
Heart failure is one of the severe diseases which menace the human health and affect millions of people. Half of all patients diagnosed with heart failure die within four years. For the purpose of avoiding life-threatening situations and minimizing the costs, it is important to predict mortality rates of heart failure patients. As part of a HEIF-5 project,(More)
The prevalence of heart failure is 2-3% of the adult population and it is expected to grow. Half of all patients diagnosed with it die within four years. To minimize lifethreatening situations and to minimize costs, it is interesting to predict mortality rates for a patient with heart failure. In this paper, a fuzzy decision tree based on classification(More)
Online social networks have billions of users worldwide when combined and they still keep increasing this amount. Their users typically develop trust relationships with the accounts of other users. But large numbers of users and potential gains from abuses of the trust relationships have attracted the attention of cyber-criminals. Therefore, it is important(More)
Cardiovascular disease is the principal cause of death in most European countries and may have a major negative impact on the patients’ functional status, productivity, and quality of life. It seems an automatic decision support system could lower these negative impacts. The current development stage of a patient-centric solution for remote management and(More)