Application of Data Mining Technique for Diagnosis of Posterior Uveal Melanoma

Article type: Research Article

Authors: Jegelevičius, Darius | Lukoševičius, Arūnas | Paunksnis, Alvydas | Barzdžiukas, Valerijus

Affiliations: Institute of Biomedical Engineering, Kaunas University of Technology, Studentų 50–343, LT-3031 Kaunas, Lithuania. E-mail: arunas.lukosevicius@ktu.lt | Department of Ophthalmology, Institute for Biomedical Research, Kaunas University of Medicine, Eiveniu 4, LT-3007 Kaunas, Lithuania. E-mail: apaun@medi.lt

Abstract: Application of knowledge discovery in databases (data mining) for medical decision support is discussed in this work. The aim of the study was to use decision support algorithm for the differential diagnosis of intraocular tumors using parameters from eye images obtained by the ultrasound examination. Application of predictive modeling algorithm for decision tree formation using See5.0/C5.0 data mining system is presented. The decision tree was build using tumor geometry and microstructure parameters. The use of decision tree allows to differentiate tumors from other tumor-like formations. Low percentage of diagnostic errors shows that decision tree is reliable enough to offer it as “second opinion” for physician's decision support.

Keywords: ophthalmic oncology, posterior uveal melanoma, ophthalmic ultrasound, data mining, decision tree

DOI: 10.3233/INF-2002-13406

Journal: Informatica, vol. 13, no. 4, pp. 455-464, 2002