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Artificial intelligence model analyzes pathology slides to predict colorectal cancer recurrence
Colorectal cancers (CRCs) can vary considerably from patient to patient, making histologic interpretation complex. To aid in interpreting H&E slides, researchers have developed QuantCRC, a quantitative segmentation algorithm that assesses known histologic features in digitized CRC images. This analysis can provide useful information to help guide therapy and surveillance in CRC.