PPEF-MBCD: A Privacy-Preserving Explainable Federated Multimodal Deep Learning Framework for Intelligent Breast Cancer Diagnosis Using Adaptive Cross-Modal Attention and Uncertainty-Aware Clinical Decision Support

Authors

  • Gunthati Pratap, Dr. Ranga Swamy Sirisati

Keywords:

Breast Cancer Diagnosis; Federated Learning; Explainable Artificial Intelligence; Multimodal Deep Learning; Adaptive Attention; Privacy-Preserving Healthcare

Abstract

Breast cancer is still one of the main causes of death in women due to cancer in the world, sothe accuracy, comprehensibility and privacy protection of a diagnostic system are crucial. Theproposed Privacy-Preserving Explainable Federated Multimodal Breast Cancer Diagnosis (PPEF-MBCD) system exploits multimodal data of mammography

References

[1] Sneha M Kuriakose, Jaseena K U, Naveen G Basil Paul, "Towards Accurate and Interpretable Breast Cancer Detection: A Transfer

Learning-Based Approach", 2026 International Conference on Innovative Trends in Information Technology (ICITIIT), pp.1-9, 2026.

[2] Radhey Shyam, Megha Pant, Mohammad Monis Khan, "Breast Cancer Detection and Classification Using ML Techniques", Artificial

Intelligence: Theory and Applications, vol.5588, pp.47, 2025.

Downloads

Published

2026-07-17

How to Cite

Gunthati Pratap, Dr. Ranga Swamy Sirisati. (2026). PPEF-MBCD: A Privacy-Preserving Explainable Federated Multimodal Deep Learning Framework for Intelligent Breast Cancer Diagnosis Using Adaptive Cross-Modal Attention and Uncertainty-Aware Clinical Decision Support . Journal of Computational Analysis and Applications (JoCAAA), 35(7), 124–147. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/5706

Issue

Section

Articles