ITDS | SPMS

AI WEB-BASED APPLICATION FOR NON-SMALL CELL LUNG CANCER

Project Description
Supervisor

Cancer related deaths, Lung cancer is the one of the most common causes of deaths; among the recurring types of lung cancer Non-Small Cell Lung Cancer (NSCLC) takes first position. A timely diagnosis will help in the improved treatment and survival of the patients. The paper at hand will demonstrate how an Artificial Intelligence (AI) Convolutional Neural Network (CNN) can be utilized to identify the subtypes of NSCLC based on the CT scan of the chest images. Scaling, normalization and data augmentation of images that make the system preprocessing methods that generate a more effective model, and reduce overfitting are constituents of the system. The trained model was very accurate and a web-based, interactive solution was trained to help the clinical application in various geographical locations and in real-time. The clinicians and the patients can pin up the CT images and obtain the real-time predictions of the diagnosis using the application that can be visually viewed using heatmaps. The aspect increases the belief and awareness of AI outcomes. The study represents the disruptive quality of deep learning in the direction of radiological diagnostics efficiency, particularly in the areas which are resource emaciated. The future directions of research will focus on scaling the system to additional lung diseases, integrating multi-modalities of clinical data, and increasing the ability of the model to generalize to other applications other than lung disease.

Web App Development: Web Development research in Computer Science and Information Technology focuses on the design, creation, and optimization of websites and web applications that are accessible over the internet or private networks. This research area spans a variety of topics, including front-end and back-end development, web frameworks, web performance, user experience (UX) design, security, and emerging web technologies. Front-end development research explores the design and functionality of the user-facing side of web applications. This involves studying languages such as HTML, CSS, and JavaScript, as well as popular frameworks like React, Angular, and Vue.js, which help create dynamic, responsive, and interactive user interfaces. Researchers in this area often focus on improving the accessibility and usability of websites across different devices and browsers. Back-end development focuses on the server side of web applications, where databases, server logic, and application functionality are managed. Research in this area includes database management, server configuration, APIs (Application Programming Interfaces), and the use of frameworks such as Node.js, Django, and Ruby on Rails. It also involves optimization of server-side processes to handle large-scale traffic, improve load times, and ensure seamless data processing.

The general objective of the work is to create a web-based AI system capable of using CNN to accurately predict the likelihood of lung cancer in patients based on their CT scan images.

2024/2025

Feb 11, 2026

1. TOURE MARIAM (UEB3248323) 2. OWUSU GYAMFI KWAME (UEB3279223) 3. OSEW RHODA SARPOMAA (UEB3218921) 4. TWUM-BARIMAH ONASIS NANA OFORI (UEB3239023)

BSc Information Technology