most citedPredicting microsatellite instability and key biomarkers in colorectal cancer from H&E-stained images: Achieving SOTA predictive performance with fewer data using Swin Transformer

35 citations

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2 papers

q-bio.QM2022★ 35 cited

Predicting microsatellite instability and key biomarkers in colorectal cancer from H&E-stained images: Achieving SOTA predictive performance with fewer data using Swin Transformer

Bangwei Guo, Xingyu Li, Jitendra Jonnagaddala +2

Artificial intelligence (AI) models have been developed for predicting clinically relevant biomarkers, including microsatellite instability (MSI), for colorectal cancers (CRC). How…

cs.CV2021★ 22 cited

Incremental Learning for Multi-organ Segmentation with Partially Labeled Datasets

Pengbo Liu, Li Xiao, S. Kevin Zhou

There exists a large number of datasets for organ segmentation, which are partially annotated, and sequentially constructed. A typical dataset is constructed at a certain time by c…