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

Many artificial intelligence models have been developed to predict clinically relevant biomarkers for colorectal cancer (CRC), including microsatellite instability (MSI). However, existing deep learning networks require large training datasets, which are often hard to obtain. In this study, based on...

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Detalles Bibliográficos
Autores principales: Guo, Bangwei, Li, Xingyu, Yang, Miaomiao, Jonnagaddala, Jitendra, Zhang, Hong, Xu, Xu Steven
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2023
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10073932/
https://www.ncbi.nlm.nih.gov/pubmed/36723384
http://dx.doi.org/10.1002/cjp2.312

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10073932/
https://www.ncbi.nlm.nih.gov/pubmed/36723384
http://dx.doi.org/10.1002/cjp2.312

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