Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 31160815.
- Also identified by DOI 10.1038/s41591-019-0462-y and PMC identifier 7423299.
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Abstract
Microsatellite instability determines whether patients with gastrointestinal cancer respond exceptionally well to immunotherapy. However, in clinical practice, not every patient is tested for MSI, because this requires additional genetic or immunohistochemical tests. Here we show that deep residual learning can predict MSI directly from H&E histology, which is ubiquitously available. This approach has the potential to provide immunotherapy to a much broader subset of patients with gastrointestinal cancer.
Medical subject headings
- Deep Learning
- Gastrointestinal Neoplasms
- Microsatellite Instability