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3. A clinical decision support system optimising adjuvant chemotherapy for colorectal cancers by integrating deep learning and pathological staging markers: a development and validation study

5. Identification of Subtypes of Barrett’s Esophagus and Esophageal Adenocarcinoma Based on DNA Methylation Profiles and Integration of Transcriptome and Genome Data

6. Deep learning for prediction of colorectal cancer outcome: a discovery and validation study

7. Identification of Prognostic Phenotypes of Esophageal Adenocarcinoma in 2 Independent Cohorts

8. Chromatin organisation and cancer prognosis: a pan-cancer study

14. 279 The Stem Cell Organization, and the Proliferative and Gene Expression Profile of Barrett's Epithelium, Indicates Its Origin From Gastric Glands

15. International study group on rectal cancer regression grading: interobserver variability with commonly used regression grading systems

16. Consensus Statements for Management of Barrett's Dysplasia and Early-Stage Esophageal Adenocarcinoma, Based on a Delphi Process

21. 902 Investigating Clonal Competition in Barrett's Associated Tumorigenesis Using Spatial Maps of Genetic Heterogeneity

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