Integrating Multiomics and Whole Slide Imaging for Predicting the Malignant Transformation of Precancerous Rectal Lesions
Abstract
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.
Fields of Study & Subjects
AI in cancer detection
Colorectal Cancer Screening and Detection
Radiomics and Machine Learning in Medical Imaging
Publication details
- Journal / source
- Cancer Screening and Prevention
- Volume
- 5
- Issue
- 1
- Pages
- 23–35
- Publication date
- 27 February 2026
- Language
- EN