Skin Cancer Classification and Detection Using Federated Learning

Malliga Subramanian, Kalaivani B, Jeevasree G, Mathan Kumar A, Nandhini P S

2025

Abstract

Detecting skin cancer involves challenges like ensuring the secure and private handling of sensitive medical data. Traditionally, centralized models have been used for classification and diagnosis, but these can risk data leaks and compromise patient privacy. To address this, a distributed learning system is proposed, allowing data to remain private while maintaining model accuracy. In this paper, we introduce a federated learning model for skin cancer classification. This system uses four independent clients: two trained on the ISIC 2018 dataset (with 7 skin disease types) and two trained on the ISIC 2019 dataset (with 8 disease types). The weights from the clients are combined and updated using the FedAvg algorithm to create a global model without sharing raw data between clients. The clients use CNN and MobileNetV2 for building the classifiers. This federated learning approach not only ensures data privacy but also achieves better performance, surpassing the current state-of-the-art accuracy for skin cancer classification across different datasets

Paper Citation

in Harvard Style

Subramanian M., B K., G J., A M. and P S N. (2025). Skin Cancer Classification and Detection Using Federated Learning. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 31-40. DOI: 10.5220/0013586200004664

in Bibtex Style

@conference{incoft25,
author={Malliga Subramanian and Kalaivani B and Jeevasree G and Mathan Kumar A and Nandhini P S},
title={Skin Cancer Classification and Detection Using Federated Learning},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT},
year={2025},
pages={31-40},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013586200004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT
TI - Skin Cancer Classification and Detection Using Federated Learning
SN - 978-989-758-763-4
AU - Subramanian M.
AU - B K.
AU - G J.
AU - A M.
AU - P S N.
PY - 2025
SP - 31
EP - 40
DO - 10.5220/0013586200004664
PB - SciTePress