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Development and external validation of a pretrained deep learning model for the prediction of non-accidental trauma
Non-accidental trauma (NAT) is deadly and difficult to predict. Transformer models pretrained on large datasets have recently produced state of the art performance on diverse prediction tasks, but the optimal pretraining strategies for diagnostic predictions are not known. Here we report the develop...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10356774/ https://www.ncbi.nlm.nih.gov/pubmed/37468526 http://dx.doi.org/10.1038/s41746-023-00875-y |