Robustly federated learning model for identifying high-risk patients with postoperative gastric cancer recurrence
Abstract The prediction of patient disease risk via computed tomography (CT) images and artificial intelligence techniques shows great potential. However, training a robust artificial intelligence model typically requires large-scale data support. In practice, the collection of medical data faces ob...
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| Autori principali: | , , , , , , , , , , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Nature Portfolio
2024-01-01
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| Serie: | Nature Communications |
| Accesso online: | https://doi.org/10.1038/s41467-024-44946-4 |
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