![]() Marsh III is sub-divided into IIIa (partial villus atrophy), Marsh IIIb (subtotal villous atrophy), and Marsh IIIc (total villus atrophy) to explain the spectrum of villus atrophy along with crypt hypertrophy and increased intraepithelial lymphocytes. Typically, CD rapidly progress from Marsh I to IIIa. CD is a chronic autoimmune disease that affects the small intestine genetically predisposed children and adults. RMDL combines different architectures and structures of deep learning and the final output of the model is based on the majority vote. Random Multimodel Deep Learning (RMDL) architecture has been used as another approach to mitigate the effects of the staining problem. To solve this problem, we use color balancing in order to train our model with a varying range of colors. ![]() The dataset used in this research is collected from different centers with different staining standards. First, the diagnosis between CD, EE, and Normal biopsies is considered, but the main challenge with this diagnosis technique is the staining problem. ![]() In the current study, we propose four diagnosis techniques for these diseases and address their limitations and advantages. Both conditions require a tissue biopsy for diagnosis and a major challenge of interpreting clinical biopsy images to differentiate between these gastrointestinal diseases is striking histopathologic overlap between them. ![]() Celiac Disease (CD) and Environmental Enteropathy (EE) are common causes of malnutrition and adversely impact normal childhood development.
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