Digestive, Oral, and Skin Physiology Commons^™

Machine Learning Approach To Distinguish Ulcerative Colitis And Crohn’S Disease Using Smote (Synthetic Minority Oversampling Technique) Methods, Kris Ghimire, Walter Lai, Yasser Omar, Thad Schwebke, Jamie Vo

SMU Data Science Review

Irritable Bowel Disease (IBD) affects a sizable portion of the US population, causing symptoms such as vomiting, abdominal pain, and diarrhea. Despite the disease’s prevalence, the precise cause is not fully understood. This study consists of endoscopic and histological data from patients diagnosed with IBD and a control population for reference. The machine learning models' focus is to classify patients into IBD types. Several models were analyzed, including decision trees, logistic regression, and k-nearest neighbors. In addition, various methods of SMOTE were applied to determine the most effective transformation and ensuring that the dataset is balanced. The best model with …