Researchers developed and validated an AI model that simultaneously detects multiple genetic markers in colorectal cancer tissue slides.
Key Details
- 1Study led by EKFZ for Digital Health at TU Dresden analyzed nearly 2,000 digitized pathology slides across seven independent cohorts in Europe and the US.
- 2The AI 'multi-target transformer' model predicts a wide range of genetic alterations, including microsatellite instability and BRAF/RNF43 mutations, from routine histological sections.
- 3Model performance matched or exceeded single-target models for key biomarkers and revealed the ability to identify shared morphological patterns tied to multiple mutations.
- 4Findings published in The Lancet Digital Health, with plans to extend methods to other cancers.
- 5Collaboration involved multiple academic centers, highlighting interdisciplinary and international partnership.
Why It Matters
This work represents a substantial advance for digital pathology and AI-driven precision diagnostics, potentially enabling faster, more comprehensive, and scalable assessment of genetic biomarkers directly from standard tissue images. Faster and lower-cost pre-screening for key mutations could streamline patient selection for molecular testing and personalize colorectal cancer care.
Source
EurekAlert
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