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Integrating Deep Learning Algorithms into a Web Application for Accurate Melanoma Skin Cancer Detection

Bichchal, Bhagyalakshmi Shridhar (2024) Integrating Deep Learning Algorithms into a Web Application for Accurate Melanoma Skin Cancer Detection. Masters thesis, Dublin, National College of Ireland.

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Abstract

Melanoma, an aggressive form of skin cancer, is known to be one of the deadliest forms of skin cancer if not detected accurately. Early detection is paramount, as early detection of melanoma offers a much better prognosis. However, traditional diagnostic techniques, such as visual diagnosis or dermoscopy, rely heavily on the experience of the examiner and can result in irregular diagnostic results or a delay in diagnosis. This study investigates the possibility of using deep learning models to recognize melanoma, which may enhance diagnostic preciseness. In this research, four deep learning models were implemented and evaluated including Custom CNN, MobileNet, VGG-19, and DenseNet121 using a variety of metrics, such as accuracy, precision, recall, and F1-score. Among the models, VGG-19 delivered the best results, achieving 88.75% accuracy on the test dataset. The primary contributions of this research are the detailed comparison of these models for melanoma classification and the successful deployment of the VGG-19 model as a web application for melanoma diagnosis. The benefits of this work include the development of a user-friendly web application using Python and Flask where the user can upload an image for an instant diagnosis, providing an accessible and accurate tool for the early detection of melanoma, and potentially saving lives.

Item Type: Thesis (Masters)
Supervisors:
Name
Email
Del Rosal, Victor
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Q Science > Life sciences > Medical sciences > Pathology > Tumors > Cancer
Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions: School of Computing > Master of Science in Artificial Intelligence
Depositing User: Ciara O'Brien
Date Deposited: 11 Aug 2025 15:29
Last Modified: 11 Aug 2025 15:29
URI: https://norma.ncirl.ie/id/eprint/8497

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