Soheil Saghafi, Timothy Rumbell, et al.
Bulletin of Mathematical Biology
Chronic gastrointestinal (GI) conditions, such as inflammatory bowel diseases (IBD), offer a promising opportunity to create classification systems that can enhance the accuracy of predicting the most effective therapies and prognosis for each patient. Here, we present a novel methodology to explore disease subtypes using our open-sourced BiomedSciAI toolkit. Applying methods available in this toolkit on the UK Biobank, including subpopulation-based feature selection and multi-dimensional subset scanning, we aimed to discover unique subgroups from GI surgery cohorts. Of a 12,073-patient cohort, a subgroup of 440 IBD patients was discovered with an increased risk of a subsequent GI surgery (OR: 2.21, 95% CI [1.81-2.69]). We iteratively demonstrate the discovery process using an additional cohort (with a narrower definition of GI surgery). Our results show that the iterative process can refine the subgroup discovery process and generate novel hypotheses to investigate determinants of treatment response.
Soheil Saghafi, Timothy Rumbell, et al.
Bulletin of Mathematical Biology
Shashanka Ubaru, Lior Horesh, et al.
Journal of Biomedical Informatics
Matthias Reumann, Blake G. Fitch, et al.
EMBC 2009
Joshua Hui, Sarah Knoop, et al.
IHI 2012