AI-Assisted Risk Stratification in Stage II Colorectal Cancer: Multi-Institutional Validation of Semantically-Enhanced Deep Learning
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The authors aimed to develop and validate an AI-based tool, SÉMIL, for automated assessment of invasiveness in stage II colorectal cancer to improve risk stratification for treatment decisions. Their findings indicate that SÉMIL outperforms traditional methods in predicting patient outcomes and effectively stratifies high-risk patients according to established guidelines, suggesting its potential utility in clinical practice for more accurate treatment planning.
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