International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 02 | Feb-2017
p-ISSN: 2395-0072
www.irjet.net
Lung Cancer Detection using Decision Tree Algorithm Ms. Leena Patil, Ms. Aparna Sirsat, Ms. Diksha Kamble, Mr.Yogesh Pawar BE IT, Department of Information Technology, DY Patil Institute of engineering and Technology Maharashtra, India BE IT, Department of Information Technology, DY Patil Institute of engineering and Technology Maharashtra, India BE IT, Department of Information Technology, DY Patil Institute of engineering and Technology Maharashtra, India HOD,Department of Information Technology, DY Patil Institute of engineering and Technology Maharashtra, India ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract – Lung cancer, also known as lung carcinoma a malignant lung tumor characterized by uncontrolled cell growth in tissues of the lung. If left untreated, this growth can spread beyond the lung by the process of metastasis into nearby tissue or other parts of the body. Most cancers that start in the lung, known as primary lung cancers, are carcinomas. The two main types are small-cell lung carcinoma (SCLC) and non-small-cell lung carcinoma (NSCLC).Cigarette smoking is the principal risk factor for development of lung cancer. A Few popular technique are used to Detect the lungs cancer like support vector machine. (SVM), naive bayes classifier. A new approach to detect the lungs cancer by Decision tree algorithm will provide effective result as compare to other algorithm. The proposed system will enhance the performance of prediction and classification.
Figure 1.Pia chart with fraction of smokers versus
non-smokers
Lung cancer may not produce any noticeable symptoms in the early stages. In approximately 40 percent of people diagnosed with lung cancer, the diagnosis is made after the disease has advanced. In one-third of those diagnosed, the cancer has reached stage 3.
Key Words: Artificial Neural Network, Decision Tree, feed forward Neural Network.
2. DATA SET
1. INTRODUCTION
The dataset for the project is taken from the UCI Machine Learning Repository
Cancer is a group of diseases involving abnormal cell growth with the potential to spread to other parts of the body. Not all tumors are cancerous; benign tumors do not spread to other parts of the body. Possible signs and symptoms include a lump, abnormal bleeding, prolonged cough, unexplained weight loss and a change in bowel movements. While these symptoms may indicate cancer, they may have other causes.[3] Over 100 types of cancers affect human.
https://archive.ics.uci.edu/ml/datasets/Lung+Cancer In this data set:Number of Instances: 32, Number of Attributes: 57 (1 class attribute, 56 predictive) Attribute Information: attribute 1 is the class label.
3. Lungs Cancer Detection By ANN An artificial neural network (ANN) is a massively the parallel distributed processor made up of simple processing units called neurons. The neurons have a natural capability for storing experiential knowledge and making it available for use [2].
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