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...
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| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Book |
| Published: |
Elsevier,
2022-01-01T00:00:00Z.
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| Subjects: | |
| Online Access: | Connect to this object online. |
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