Early Detection of lung Cancer Using Machine Learning Technique
Bolleddu Devananda Rao, Mohammad Yusof Arshad
Abstract
The study and diagnosis of the lung diseases is the investigating point of interest for the medical experts existing from the a foretime to the current day. A diagnostic system is required to overcome this approach to reduce the time in diagnosis of lung cancers that is putting human life at risk. Few projects are proposed for this purpose and many other are under trails. To identify the cancer cells in the CT images a neural network model is proposed. It is also used to recognize issues in therapeutic imaging applications. A framework is originated for the identification of lung cancer that includes application of deep neural network system and AI. For staging of lung cancer classification of CNN is required. Deep learning methods are used on supervised learning to obtain better results. The proposed framework includes neural network that comprises of many steps like collection of images, pre-preparation, pixel enhancement, segmentation of images, and feature extraction. To outline the present research, it explains that to attain accurate results in detection and treatment of lung cancer cases at a low cost machine learning plays an unpredictable role.