Lung Cancer and General Disease Prediction

Lung Cancer and General Disease Prediction

Author Name : Prof. Asha P. , Rahila Fatima

ABSTRACT Lung cancer is a leading cause of cancer-related deaths worldwide. Early detection and treatment are critical for improving patient outcomes. In this study, we aimed to develop and evaluate a machine learning-based approach for predicting the likelihood of lung cancer in patients. We collected clinical and imaging data from a large cohort of patients with suspected lung cancer. The dataset was split into training and validation sets. We trained several machine learning algorithms including random forest classifier, Gaussian NB, and Support Vector Machine on the training set and evaluated their performance on the validation set. We also conducted feature importance analysis to identify the most important predictors of lung cancer. Our results show that by using CT scan images we can detect whether the cancerous cells are bengin case, malignant case or normal case cells.