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AI framework integrates WSI and multiomics data to predict malignant transformation in rectal lesions, indicating improved diagnostic accuracy.
Predicting the malignant transformation of rectal precancerous lesions remains challenging because conventional Whole Slide Images (WSIs) capture morphological information but lack molecular insight. Multiomics data provide complementary biological signals that often precede visible morphological changes. This study aimed to develop an artificial intelligence (AI)-based multimodal framework integrating WSI and multiomics data for accurate early prediction of malignant transformation.
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Negin Amirzadeh (2026) studied this question.
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