M. S. Rahman

IMMF: An Interpretable Multi-Modal Framework for Hypothesis-Driven Biomarker Discovery in Triple-Negative Breast Cancer Using Public Data

An interpretable, multi-modal framework that integrates histopathological image analysis with multi-omics profiling, leveraging U-Net-based nuclei segmentation, vision-language models (BLIP), biomedical language models (BioGPT), and explainable AI is proposed.