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Predicting microsatellite instability and key biomarkers in colorectal cancer from H&E‐stained images: achieving state‐of‐the‐art predictive performance with fewer data using Swin Transformer
Research article (The Journal of Pathology Clinical Research, 2023) · cited 29× · AI/ML
Predicting microsatellite instability and key biomarkers in colorectal cancer from H&E‐stained images: achieving state‐of‐the‐art predictive performance with fewer data using Swin Transformer
Summary
Predicting microsatellite instability and key biomarkers in colorectal cancer from H&E‐stained images: achieving state‐of‐the‐art predictive performance with fewer data using Swin Transformer is a scholarly article[1].
Key Facts
Predicting microsatellite instability and key biomarkers in colorectal cancer from H&E‐stained images: achieving state‐of‐the‐art predictive performance with fewer data using Swin Transformer's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Predicting microsatellite instability and key biomarkers in colorectal cancer from H&E‐stained images: achieving state‐of‐the‐art predictive performance with fewer data using Swin Transformer. Retrieved May 24, 2026, from https://4ort.xyz/entity/predicting-microsatellite-instability-and-key-biomarkers-in-colorectal-cancer-from-h-amp-estained-images-achieving-state
MLA“Predicting microsatellite instability and key biomarkers in colorectal cancer from H&E‐stained images: achieving state‐of‐the‐art predictive performance with fewer data using Swin Transformer.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/predicting-microsatellite-instability-and-key-biomarkers-in-colorectal-cancer-from-h-amp-estained-images-achieving-state.
BibTeX@misc{4ortxyz_predicting-microsatellite-instability-and-key-biomarkers-in-colorectal-cancer-from-h-amp-estained-images-achieving-state_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Predicting microsatellite instability and key biomarkers in colorectal cancer from H&E‐stained images: achieving state‐of‐the‐art predictive performance with fewer data using Swin Transformer}}, year = {2026}, url = {https://4ort.xyz/entity/predicting-microsatellite-instability-and-key-biomarkers-in-colorectal-cancer-from-h-amp-estained-images-achieving-state}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Predicting microsatellite instability and key biomarkers in colorectal cancer from H&E‐stained images: achieving state‐of‐the‐art predictive performance with fewer data using Swin Transformer — https://4ort.xyz/entity/predicting-microsatellite-instability-and-key-biomarkers-in-colorectal-cancer-from-h-amp-estained-images-achieving-state (retrieved 2026-05-24)
