Classification of Cancer of The Lungs Using SVM and ANN - Fenwa, Olusayo Deborah; A. Ajala, Funmilola; A. Adigun, Adebisi (INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 2015)
Accurate diagnosis of cancer plays an important role in order to save human life. The results of the diagnosis indicate by the medical experts are mostly differentiated based on the experience of different medical experts. This problem could risk the life of the cancer patients. A fast and effective method to detect the lung nodules and separate the cancer images from other lung diseases like tuberculosis is becoming increasingly needed due to the fact that the incidence of lung cancer has risen dramatically in recent years and an early detection can save thousands of lives each year. The focus of this paper is to compare the performance of the ANN and SVM classifiers on acquired online cancer datasets. The performance of both classifiers is evaluated using different measuring parameters namely; accuracy, sensitivity, specificity, true positive, true negative, false positive and false negative.