Predicting clinical endpoints and visual changes with quality-weighted tissue-based renal histological features
Two common obstacles limiting the performance of data-driven algorithms in digital histopathology classification tasks are the lack of expert annotations and the narrow diversity of datasets. Multi-instance learning (MIL) can address the former challenge for the analysis of whole slide images (WSI),...
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| Главные авторы: | , , , , , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Frontiers Media S.A.
2024-04-01
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| Серии: | Frontiers in Transplantation |
| Предметы: | |
| Online-ссылка: | https://www.frontiersin.org/articles/10.3389/frtra.2024.1305468/full |
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