Automatic Identification of Cancer Affect in Lungs Using Machine Learning Algorithm

Lung cancer has become one of the serious type of cancer that provides lots of life threatening problems in recent days. Various technologies are employed to make the medical equipment and analysis systems on effective identification of lung tumor. Consider the lungs tumor in the early stages and make the diagnostic procedures accurately to remove the lungs tumor from the organs and make the functionality of the organs as normal humans. Early detection of lung tumor is important to treat and make the successful results in shorter time. The presented method considered lightweight analysis module for making lung lesions present in the organs and further discriminating the lung tumor using dataset collected from the cancer affected patients. The proposed method is implemented using customized Multi-feature enabled support vector machine (MFE-SVM) algorithm to categorize the lung lesions. The input images are collected from UCI repository and standard medical websites which are publicly available. Input images are processed well to have the affected region to be classified using NOVEL MFE-SVM algorithm. The presented system achieved 98.41% accuracy and compared with various states of art approaches.