Categorization & Recognition of Lung Tumor Using Machine Learning Representations.

CONCLUSION: The proposed method will efficiently identify the position of the tumor in lungs using the probability framework. This will offer a promising outcome for recognition and diagnosis of lung cancer. In this manuscript, GLCM features are used for the prediction of lung tumor and tests are performed for performance analysis in comparison with the histogram and GLCM features, in which GLCM features are accurate in predicting lung tumor even if it takes more time than histogram features. In this manner, early discovery and probability of lung cancer should assume a crucial task in finding a procedure and furthermore, an increment in the survival rate of the patient. This exploration investigates machine learning systems which consider quality articulation, to perceive cancer or to identify lung cancer. PMID: 31989910 [PubMed - in process]
Source: Current Medical Imaging Reviews - Category: Radiology Tags: Curr Med Imaging Rev Source Type: research