Machine Learning Approaches in Inflammatory Bowel Disease

The great flow of clinical data can be managed with efficiency and effectiveness, improving the speed of interpretation of information, through Machine Learning (ML) methodologies, aimed at overcoming the barriers present in the diagnosis and treatment processes of patients, such as those affected by Inflammatory Bowel Disease (IBD). In this paper we survey relevant ML applications used for managing the large flow of clinical data and for overcoming the barriers present in the diagnosis and treatment processes of patients, with special focus on IBD. In IBD settings, main data sources include cohort study data, administrative databases, e-Health applications, Electronic Health Records (EHR), medical image data, Omics data, Clinical trial data and social media data. Potential applications for overcoming barriers in the field of IBD are also discussed.