The information shows that there were 2.2 million new belongings of lung cancer in 2023.Its quantity is still rising yearly. As a result, it has become an extremely significant issue how to identify the sickness in time. Based on the proposed VGG16 Convolutional Neural Network (CNN), research created a neural network. The trained model to divide the computed tomography (CT) scan descriptions of lung cancer into four categories. To avoid over fitting, added to the dataset using random cropping, flipping, etc. from the Kaggle database. The trained model was then combined with a chatbot and graphical user interface. More specifically, created the user interface and implemented it on a website using the Django frameworks and MySQL database. Also, included certain Natural Language Processing (NLP) tools in the chatbot, including decision trees and Name Entity Recognition (NER). The results of the tests show that neural network performs well. Also, user interface will make it easier for folks who are not familiar with deep learning to understand the conditions. © 2024 Elsevier B.V., All rights reserved.