NSF-SNSF:Learning disentangled graph representations for biomedicine — NSF Award to Michigan State University (MI, $400,000)
With the recent advances in multimodal data acquisition technologies in healthcare, diverse and large volumes of biological omics, imaging and physiological data are collected at an exponentially increasing rate. The availability of this vast amount of data has allowed us to expand our understanding of physiological an
| Award title | NSF-SNSF:Learning disentangled graph representations for biomedicine |
|---|---|
| Award ID | 2430516 |
| Awardee | Michigan State University |
| City | EAST LANSING |
| State | MI |
| Amount obligated | $400,000 |
| Principal investigator | Selin Aviyente |
| Program | CSCS: Circuits and Systems for |
| Start date | 01/01/2025 |
| Abstract | With the recent advances in multimodal data acquisition technologies in healthcare, diverse and large volumes of biological omics, imaging and physiological data are collected at an exponentially increasing rate. The availability of this vast amount of data has allowed us to expand our understanding of physiological and pathological processes, enabling the development of novel healthcare solutions. However, this abundance of data also presents major challenges in analysis due to its complexity a |
| Source | NSF Awards |
$799/mo
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