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Empowering digital pathology applications through explainable knowledge extraction tools
Exa-scale volumes of medical data have been produced for decades. In most cases, the diagnosis is reported in free text, encoding medical knowledge that is still largely unexploited. In order to allow decoding medical knowledge included in reports, we propose an unsupervised knowledge extraction sys...
| Autores principales: | , , , , , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9577130/ https://www.ncbi.nlm.nih.gov/pubmed/36268087 http://dx.doi.org/10.1016/j.jpi.2022.100139 |