PARALLEL ALGORITHMS FOR PULMONARY NODULE CLASSIFICATION WITH THE HELP OF BAYES THEOREM
European Journal of Molecular & Clinical Medicine,
2020, Volume 7, Issue 9, Pages 1394-1397
AbstractThe cancer starts in the lungs is known as lung cancer. The leading world cause of death is lung cancer. In its early stages, lung cancer does not usually cause signs and symptoms. The early diagnosis of lung cancer is required to reduce the mortality rate. A parallel algorithm for pulmonary nodule classification with the help of Bayes theorem is discussed in this study. At first parallel algorithms like task, pipeline and data parallel for feature extraction. Then Bayes theorem is used for classification. The experimental results show the performance of pulmonary nodules classification in terms of accuracy using parallel algorithms and Bayes classification.
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