MACHINE LEARNING FOR CROHN’S DISEASE PHENOTYPE MODELING USING BIOPSY IMAGES

Predicting Crohn’s disease (CD) phenotype development has proven challenging due to difficulties in biopsy image interpretation of histologically similar yet biologically distinct phenotypes. At initial diagnosis, mostly CD patients are classified as B1 (inflammatory behavior), they typically either retain B1 phenotype or develop more complicated B2 (stricturing), B3 (internal penetrating), or B2/B3 phenotypes (defined by Montreal Classification). Prediction of phenotype development based on baseline biopsies can radically improve our clinical care by altering disease management.

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