Classification techniques for non-invasive recognition of liver fibrosis stage

• Autorzy: Krawczyk B. , Woźniak M. , Orczyk T. , Porwik P. , Musialik J. , Błońska-Fajfrowska B.
• Języki publikacji: EN

Abstrakty

EN

Contemporary medicine should provide high quality diagnostic services while at the same time remaining as comfortable as possible for a patient. Therefore novel non-invasive disease recognition methods are becoming one of the key issues in the health services domain. Analysis of data from such examinations opens an interdisciplinary bridge between the medical research and artificial intelligence. The paper presents application of machine learning techniques to biomedical data coming from indirect examination method of the liver fibrosis stage. Presented approach is based on a common set of non-invasive blood test results. The performance of four different compound machine learning algorithms, namely Bagging, Boosting, Random Forest and Random Subspaces, is examined and grid search method is used to find the best setting of their parameters. Extensive experimental investigations, carried out on a dataset collected by authors, show that automatic methods achieve a satisfactory level of the fibrosis level recognition and may be used as a real-time medical decision support system for this task.

Słowa kluczowe

EN

machine learning; multiple classifier systems; compound pattern recognition; medical informatics; liver fibrosis; hepatitis C

PL

uczenie maszynowe; systemy wielo-klasyfikatorów; informatyka medyczna; zwłóknienie wątroby; wirusowe zapalenie wątroby typu C

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2012
• Tom: Vol. 20
• Strony: 121--127
• Opis fizyczny: Bibliogr. 19 poz., rys., tab.

Twórcy

autor

Krawczyk B.

• Department of Systems and Computer Networks, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370 Wroclaw, Poland

autor

Woźniak M.

autor

Orczyk T.

autor

Porwik P.

autor

Musialik J.

autor

Błońska-Fajfrowska B.

Bibliografia

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