Genomics and Translational Bioinformatics Working Group Panel: Multimodal Artificial Intelligence Models Using Multi Omics Data

Presentation Type: Panel
Presentation Time: 03:30 PM - 04:45 PM

Working Group: Genomics and Translational Bioinformatics Working Group
Primary Track: Translation Bioinformatics/Precision Medicine


Advances in high-throughput technologies have made biomedicine a profoundly data-rich field, generating diverse modalities ranging from multi-omics and single-cell profiles to imaging, clinical notes, and electronic health records. Integrating these heterogeneous datasets into models that advance biological insight and precision medicine remains a challenge. This panel, sponsored by the Genomics and Translational Bioinformatics Working Group, highlights emerging multimodal AI approaches including machine learning and large language models that combine molecular, clinical, and imaging data. Such methods promise improved disease diagnosis, deeper understanding of biological mechanisms, enhanced prediction, and accelerated biomarker and therapeutic discovery. Panelists will discuss their current research, challenges in data harmonization, interpretability, reproducibility, and clinical integration, and will outline future directions. This panel will offer a perspective on how multimodal AI can reshape translational bioinformatics and precision medicine.

Moderator:
Ece Uzun, PhD
Brown University Health/Brown University

Speaker(s):
Wenyu Song, PhD
Brigham and Women's Hospital, Harvard Medical School

Kai Wang, PhD
Children's Hospital of Philadelphia

Zhongming Zhao, PhD
University of Texas Heal Sci Ctr Houston

Ece Uzun, PhD
Brown University Health/Brown University

Author(s):
Wenyu Song, PhD - Brigham and Women's Hospital, Harvard Medical School; Alper Uzun, PhD - Brown University; Kai Wang, PhD - Children's Hospital of Philadelphia; Zhongming Zhao, PhD - University of Texas Heal Sci Ctr Houston; Ece Uzun, PhD - Brown University Health/Brown University;

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