Translating Imaging to Genomics: Leveraging Transformers for Predictive Modeling
<|reference_start|>Translating Imaging to Genomics: Leveraging Transformers for Predictive Modeling: In this study, we present a novel approach for predicting genomic information from medical imaging modalities using a transformer-based model. We aim to bridge the gap between imaging and genomics data by leveraging transformer networks, allowing for accurate genomic profile predictions from CT/MRI images. Presently most studies rely on the use of whole slide images (WSI) for the association, which are obtained via invasive methodologies. We propose using only available CT/MRI images to predict genomic sequences. Our transformer based approach is able to efficiently generate associations between multiple sequences based on CT/MRI images alone. This work paves the way for the use of non-invasive imaging modalities for precise and personalized healthcare, allowing for a better understanding of diseases and treatment.<|reference_end|>
@article{farooq2024translating,
    title={Translating Imaging to Genomics: Leveraging Transformers for Predictive
  Modeling},
    author={Aiman Farooq, Deepak Mishra, Santanu Chaudhury},
    journal={arXiv preprint arXiv:2408.00311},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.00311},
    primaryClass={cs.CV}
}