Prediction of mortality rates in heart failure patients with data mining methods

• Autorzy: Bohacik J. , Kambhampati C. , Davis D. N. , Cleland J. G. F.

Identyfikatory

DOI

10.2478/v10065-012-0046-7

• Języki publikacji: EN

Abstrakty

EN

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, a data mining study was conducted aiming specifically at extracting new knowledge from a group of patients suffering from heart failure and using it for prediction of mortality rates. The methodology of knowledge discovery in databases is analyzed within the framework of home telemonitoring. Several data mining methods such as a Bayesian network method, a decision tree method, a neural network method and a nearest neighbour method are employed. The accuracy for the data mining methods from the point of view of avoiding life-threatening situations and minimizing the costs is discussed. It seems that the decision tree method achieves the best accuracy results and is also interpretable for the clinicians.

Słowa kluczowe

EN

heart failure; data mining; prediction of mortality rates; home telemonitoring; Bayesian network method; decision tree method; neural network method; nearest neighbour method

• Wydawca: Wydawnictwo UMCS
• Czasopismo: Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica
• Rocznik: 2013
• Tom: Vol. 13, no. 1
• Strony: 7--16
• Opis fizyczny: Bibliogr. 17 poz., rys., tab.

Twórcy

autor

Bohacik J.

• Department of Computer Science, University of Hull, Hull, UK
• Department of Computer Science, University of Zilina Zilina, Slovakia

autor

Kambhampati C.

• Department of Computer Science, University of Hull, Hull, UK

autor

Davis D. N.

• Department of Computer Science, University of Hull, Hull, UK

autor

Cleland J. G. F.

• Department of Cardiology, University of Hull, Hull, UK

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