Cancer Detection Using Improved CNN-Based Models

Bo Ning

2025

Abstract

Medical imaging is a crucial part of clinical diagnosis, yet processing its large-volume data is challenging. Convolutional neural networks (CNNs) have shown great potential in medical image analysis. However, the high computational cost and need for large annotated datasets often limit their widespread clinical adoption This paper focuses on CNN-based models for cancer detection. The paper delves into various innovative models applied in breast, lung, and skin cancer detection. These newly proposed models excel in specific aspects, whether in high-precision classification, classification efficiency, or lightweight design. But some models still face issues like poor generalization on rare diseases and high computational requirements. This paper summarizes these issues and identifies current and future research directions, including the development of generalized cancer detection frameworks and the application of transfer learning techniques. Overall, the paper highlights the enormous potential of CNN-based models in medical imaging while pointing out the need for continuous research and development to overcome existing challenges and limitations.

Paper Citation

in Harvard Style

Ning B. (2025). Cancer Detection Using Improved CNN-Based Models. In Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI; ISBN 978-989-758-792-4, SciTePress, pages 138-144. DOI: 10.5220/0014323000004718

in Bibtex Style

@conference{emiti25,
author={Bo Ning},
title={Cancer Detection Using Improved CNN-Based Models},
booktitle={Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2025},
pages={138-144},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0014323000004718},
isbn={978-989-758-792-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI
TI - Cancer Detection Using Improved CNN-Based Models
SN - 978-989-758-792-4
AU - Ning B.
PY - 2025
SP - 138
EP - 144
DO - 10.5220/0014323000004718
PB - SciTePress