Lung Cancer Prediction Using Machine Learning

Abstract: Lung cancer is a major health concern and should be predicted at an earlier and precise stage to enhance outcomes for patients. This project offers a hybrid machine learning approach by integrating the analysis of symptom-based surveys and the analysis of CT scan images for risk prediction of lung cancer. Patient complaints are analyzed by a rule-based weighted scoring system to obtain a preliminary result of risk levels associated with the possibility of lungs being affected by cancer. The CT scan images are pre-processed by techniques involving the resizing and sharpening of images, applying threshold levels, and edges for extracting significant details, which are then processed by ResNet50 for extracting the extracted featured details by a Convolutional Neural Network (CNN).

Keywords: Machine Learning, CNN, ResNet50, Image Preprocessing.