Lung cancer prediction system using CT scans and symptoms

Abstract

The main objective of the graduate project is to explore deep learning models for aiding in the detection of lung cancer from CT scans and symptoms. This application aims to revolutionize lung cancer prediction by harnessing the power of both symptom analysis for normal users and advanced CT scans image analysis for doctors. For normal users, the application explores the analysis of symptoms and risk factors commonly associated with lung cancer. This empowers individuals to be proactive about their health, seek appropriate medical attention, and undergo further diagnostic tests if necessary. Concurrently, for doctors and healthcare professionals, the project focuses on the analysis of CT scans images, a powerful tool in lung cancer diagnosis, enabling early detection of lung cancer, and ultimately, improving patient outcomes and survival rates.