Lung cancer has been one of the deadliest diseases in today’s decades. It has become one of the causes of death in both man and woman. There are various reasons for which lung cancer occurs but classification of tumor and predicting it in the right stage is the most important part. This paper focused on the numerous approaches has been derived for lung cancer detection from different literature survey to advance the ability of detection of cancer. Digital image processing and data mining both are equally important because for prediction either image dataset or statistical dataset is used so for pre-processing the image dataset digital image processing is applied for statistical dataset data mining is applied. After pre-processing, segmentation and feature extraction we apply various machine learning algorithm for the prediction of lung cancer. So first we have provided a sketch of Machine learning and then various fields like in image data or statistical data where machine learning has been used for classification. Once the classification is done confusion matrix is generated for calculating accuracy, sensitivity, precision, these method is used to measure the rate of accuracy of the proposed model.
This work is focused on lung cancer prediction using machine learning technique. Lung cancer is one of the widespread diseases due to the growth of irregular cell in both the lungs as a result of which this irregular cell starts growing into tumour, and this tumour can be cancerous as well as non-cancerous. In the traditional approach CT scan images has been used based on the report image segmentation has been done to remove the noise so that a clear picture can be generated to detect the location of tumor. Once the location is known then classification or clustering approach can be used to predict the stage of cancer. Previously supervised machine learning algorithm has been used to predict lung cancer. In this work a prediction model is proposed that is based on the median filter, watershed segmentation, and then feature extraction has done like texture and region. And on the extracted feature classification technique was applied for prediction of cancer.
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