Journal of Cancer Diagnosis
Open Access

A Multimodal AI-Based Diagnostic Framework for Early Detection of Breast, Colon, and Cervical Cancers Using Imaging and Genomic Data Fusion

Radhika Menon^*

Department of Computational Biology, Indian Institute of Science, Bangalore, India

Received Date: Mar 01, 2025 / Accepted Date: Mar 31, 2025 / Published Date: Mar 31, 2025

Citation: Radhika M (2025) A Multimodal AI-Based Diagnostic Framework for EarlyDetection of Breast, Colon, and Cervical Cancers Using Imaging and GenomicData Fusion. J Cancer Diagn 9: 284.

Copyright: © 2025 Radhika M. This is an open-access article distributed underthe terms of the Creative Commons Attribution License, which permits unrestricteduse, distribution, and reproduction in any medium, provided the original author andsource are credited.

To read the full article Peer-reviewed Article PDF

Cancer remains a major global health burden, with breast, colon, and cervical cancers among the leading causes of mortality in women worldwide. Despite advancements in diagnostic imaging and genomics, early and accurate detection continues to be a challenge, especially in low-resource settings. This paper proposes a novel multimodal AI-based diagnostic framework that integrates medical imaging and genomic data using advanced machine learning and deep learning algorithms. By fusing these complementary data sources, the proposed system aims to enhance the sensitivity and specificity of cancer detection during the early stages, thereby improving prognosis and survival rates.