Designed a framework integrating transcriptomics, imaging, and clinical attributes to improve hepatocellular carcinoma diagnosis and prediction.
Abstract
This work presents a multi-modal fusion framework that combines transcriptomic data, medical imaging, and clinical attributes to enhance the accuracy of hepatocellular carcinoma (HCC) diagnosis and prediction. The integrated approach provides a comprehensive view of disease progression and improves diagnostic capabilities.
Conference
Presented at International Conference for Genomic Medicine 2026 (ICGM 2026) Submitted at AASLD (American Association for the Study of Liver Diseases) 2025.