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),...
| Päätekijät: | , , , , , , |
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| Aineistotyyppi: | Journal article |
| Kieli: | English |
| Julkaistu: |
Frontiers Media
2024
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