Histopathological Imaging Dataset for Oral Cancer Analysis: A Study with a Data Leakage Warning

Marcelo Nogueira, Marcelo Nogueira, Elsa Gomes, Elsa Gomes

2025

Abstract

Oral squamous cell carcinoma is one of the most prevalent and lethal types of cancer, accounting for approximately 95% of oral cancer cases. Early diagnosis increases patient survival rates and has traditionally been performed through the analysis of histopathological images by healthcare professionals. Given the importance of this topic, there is an extensive body of literature on it. However, during our bibliographic research, we identified clear cases of data leakage related to contamination of test data due to the improper use of data augmentation techniques. This impacts the published results and explains the high accuracy values reported in some studies. In this paper, we evaluate several models, with a particular focus on EfficientNetBx architectures combined with Transformer layers, which were trained using Transfer Learning and Data Augmentation to enhance the model’s feature extraction and attention capabilities. The best result, obtained with the Effi-cientNetB0, together with the Transformer layers, achieved an accuracy rate of 87.1% on the test set. To ensure a fair comparison of results, we selected studies that we identified as not having committed data leakage.

Paper Citation

in Harvard Style

Nogueira M. and Gomes E. (2025). Histopathological Imaging Dataset for Oral Cancer Analysis: A Study with a Data Leakage Warning. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS; ISBN 978-989-758-731-3, SciTePress, pages 811-818. DOI: 10.5220/0013382100003911

in Bibtex Style

@conference{biosignals25,
author={Marcelo Nogueira and Elsa Gomes},
title={Histopathological Imaging Dataset for Oral Cancer Analysis: A Study with a Data Leakage Warning},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS},
year={2025},
pages={811-818},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013382100003911},
isbn={978-989-758-731-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS
TI - Histopathological Imaging Dataset for Oral Cancer Analysis: A Study with a Data Leakage Warning
SN - 978-989-758-731-3
AU - Nogueira M.
AU - Gomes E.
PY - 2025
SP - 811
EP - 818
DO - 10.5220/0013382100003911
PB - SciTePress