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- W4313451412 abstract "To improve accuracy in automatic detection of Tuberculosis (TB) disease from Lung CT images. The dataset used is Chest CT scan images consisting of 1000 images. Detection of Tuberculosis is done by the Support Vector Machine Classifier (N=10) and KNN classifier. During testing, 10 iterations have been taken for each classification algorithm. The experimental results show that the Support Vector Machine algorithm with mean accuracy of 94.17% is compared with K Nearest Neigh-bour algorithm with mean accuracy of 89.84%. The statistical significance of two algorithms sig (2-tailed) p-value observed is 0.00 in the independent sample t test. Within the limitations of this study SVM has better accuracy than KNN." @default.
- W4313451412 created "2023-01-06" @default.
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- W4313451412 date "2022-10-06" @default.
- W4313451412 modified "2023-09-23" @default.
- W4313451412 title "Improved Accuracy in Automatic Detection of Tuberculosis Disease from Lung CT images using Support Vector Machine Classifier over K-Nearest Neighbours Classifier" @default.
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- W4313451412 doi "https://doi.org/10.1109/iccr56254.2022.9996067" @default.
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