application of data science in inflammatory bowel disease

This paper explores the application of the k-nearest neighbors (knn) algorithm in the field of inflammatory bowel disease (ibd). ibd is a group of chronic inflammatory disorders that affect the gastrointestinal tract. data science techniques have shown promise in identifying patterns and predicting outcomes in various medical conditions. in this study, we investigate the effectiveness of the knn algorithm in diagnosing and classifying different subtypes of ibd based on clinical and biochemical features. the results demonstrate the potential of data science and the knn algorithm in enhancing the understanding and management of ibd.