Melanoma Cancer Detection Using Deep Learning

G. Chinna Pullaiah, Vyshnavi Manchikanti, Shaguptha Naaz Dudekula, Ravi Teja Mekalappagari, Viswa Teja Devarakonda

2025

Abstract

This study explores the skin behaviour and the fact that skin cancers, especially melanoma, can be fatal; however, early detection can significantly improve the patient’s survival. This study presents a new approach, which integrates image analysis with clinical information to improve the reliability of melanoma diagnosis. Currently, dermatologists take dermoscopic photographic images of a skin lesion using a high-speed camera and obtain a diagnostic accuracy of 65-80%. In case of additional specialist evaluations, this can increase to 75-95%. This paper uses CNNs, specifically the MobileNetV2, for skin disease subtype classification. It also utilizes Linear Discriminant Analysis for their severity levels according to clinical data. The best performing accuracy for the hybrid approach was achieved using CNN, with 92.32%, higher than that with traditional image-only methodology. From being a simple custom- made application to user-friendly web application using Flask is now been developed for real-time detection to avoid manual process and reduce time period for detecting the type of melanoma. The fusion of AI technical platform and clinical curative, in this work presented, provides a viable framework for early preliminary diagnosis of melanoma, thereby promoting success and access to the healthcare system.

Paper Citation

in Harvard Style

Pullaiah G., Manchikanti V., Dudekula S., Mekalappagari R. and Devarakonda V. (2025). Melanoma Cancer Detection Using Deep Learning. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 81-87. DOI: 10.5220/0013908500004919

in Bibtex Style

@conference{icrdicct`2525,
author={G. Pullaiah and Vyshnavi Manchikanti and Shaguptha Dudekula and Ravi Mekalappagari and Viswa Devarakonda},
title={Melanoma Cancer Detection Using Deep Learning},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={81-87},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013908500004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Melanoma Cancer Detection Using Deep Learning
SN - 978-989-758-777-1
AU - Pullaiah G.
AU - Manchikanti V.
AU - Dudekula S.
AU - Mekalappagari R.
AU - Devarakonda V.
PY - 2025
SP - 81
EP - 87
DO - 10.5220/0013908500004919
PB - SciTePress