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|Title:||Examining the feasibility of predicting drug resistance of lung tuberculosis using image data|
|Authors:||Kovalev, V. A.|
Liauchuk, V. A.
Safonau, I. U.
|Keywords:||ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Кибернетика|
|Publisher:||Minsk : Publ. center of BSU|
|Citation:||Computer Data Analysis and Modeling: Theoretical and Applied Stochastics : Proc. of the Tenth Intern. Conf., Minsk, Sept. 10–14, 2013. Vol 2. — Minsk, 2013. - P. 122-125|
|Abstract:||This work is dedicated to the problem of early diagnosis of tuberculosis drug resistance using X-ray and CT images of tuberculosis patients. Image features were extracted using extended co-occurrence matrix approach followed by Prin- cipal Component Analysis method. Classification was done with help of recent classifiers such as SVM, Naive Bayesian, Logistic Regression and Linear Discrim- inant Analysis. The maximum achieved accuracy of drug resistance prediction was 75% when using SVM classifier. Results of the present study suggest that the approach may potentially be employed for early predictions of drug resistance.|
|Appears in Collections:||2013. Computer Data Analysis and Modeling. Vol 2|
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