Lung Cancer Detection Using AI

The project's goal is to improve the detection and classification of lung cancer from medical imaging through advanced artificial intelligence techniques, particularly with Convolutional Neural Networks (CNNs). The goal is to support early diagnosis, enhance the accuracy and trustworthiness of clinical evaluations, save time, make diagnostic tools more accessible, and consequently, improve patient outcomes. The system architecture includes designing a machine learning model structured around CNNs; special attention is given to the steps of data gathering, data cleaning, feature selection, and model training. The main focus of the proposed approach is the application of advanced image analysis methods on top of the classifier based on CNNs which is used to classify the images. Under the project name “Disease Detection by Artificial Intelligence,” the model provides a diagnostic accuracy rate of 94.297%, demonstrating the potential of AI-based systems to autonomously formulate and execute disease diagnosis protocols in health care frameworks.