AI Model Predicts Microsatellite Instability and Immunotherapy Response from Histology

Yonsei University researchers introduced MSI-SEER, an AI model for MSI and immunotherapy response prediction from histology images of gastric and colorectal cancers.
Key Details
- 1MSI-SEER uses deep Gaussian process modeling to analyze H&E-stained whole-slide images.
- 2The model integrates uncertainty quantification, providing a Bayesian Confidence Score for each prediction.
- 3MSI-SEER flags uncertain cases for human review to enhance reliability and safety.
- 4Validated on large, racially diverse datasets, it achieved state-of-the-art MSI prediction accuracy.
- 5The model also predicts immune checkpoint inhibitor (ICI) response, integrating tumor MSI status and stroma-to-tumor ratio.
- 6Published in npj Digital Medicine on May 19, 2025.
Why It Matters

Source
EurekAlert
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