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Deep learning-derived splenic radiomics, genomics, and coronary artery disease.

Meghana KamineniVineet RaghuBuu TruongAhmed AlaaArt SchuermansSam FriedmanChristopher ReederRomit BhattacharyaPeter LibbyPatrick T EllinorMahnaz MaddahAnthony PhilippakisWhitney HornsbyZhi YuPradeep Natarajan
Published in: medRxiv : the preprint server for health sciences (2024)
Our study, combining deep learning with genomics, presents a new framework to uncover the splenic axis of CAD. Notably, our study provides evidence for the underlying genetic connection between the spleen as a candidate causal tissue-type and CAD with insight into the mechanisms of 9p21, whose mechanism is still elusive despite its initial discovery in 2007. More broadly, our study provides a unique application of deep learning radiomics to non-invasively find associations between imaging, genetics, and clinical outcomes.
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