# Clinically Oriented AI Model for Intraoperative Pathology

Digest AI · Generative AI & Models · published 2026-09-10T00:00:00Z

Canonical: https://digestai.news/story/clinically-oriented-ai-model-for-intraoperative-pathology

## Summary

Researchers have developed CRISP, a foundation model designed to support intraoperative pathology in precision surgery. CRISP was trained on over 100,000 frozen sections from ten medical centers and evaluated on nearly 15,000 intraoperative slides. It demonstrated robust generalization across six institutions, 14 tumor types, and 24 anatomical sites, including previously unseen sites and rare cancers. In a prospective cohort of over 3,000 patients, CRISP sustained high diagnostic accuracy, informing surgical decisions in 92.6% of cases. Human-AI collaboration further reduced diagnostic workload by 35%, avoided 105 ancillary tests, and enhanced detection of micrometastases with 87.5% accuracy. This model represents a significant step towards integrating AI-driven intraoperative pathology into clinical practice, supporting surgical decision-making and improving patient outcomes.

## Key points

- CRISP trained on over 100,000 frozen sections from ten medical centers
- Evaluated on nearly 15,000 intraoperative slides
- Demonstrated robust generalization across six institutions, 14 tumor types, and 24 anatomical sites

## Why it matters

This model could revolutionize intraoperative pathology by providing accurate and timely diagnostic support, potentially reducing diagnostic workload and ancillary tests, and improving patient outcomes.

## Sources

1. [A clinically-oriented foundation model for intraoperative pathology](https://nature.com/articles/s41591-026-04703-0) (Nature Machine Learning, 2026-09-10, primary source)

## Cite

Digest AI, "Clinically Oriented AI Model for Intraoperative Pathology", 10 September 2026, https://digestai.news/story/clinically-oriented-ai-model-for-intraoperative-pathology

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