Gene Identification in Inflammatory Bowel Disease via a Machine Learning Approach.

ABSTRACT: Inflammatory bowel disease (IBD) is an illness with increasing prevalence, particularly in emerging countries, which can have a substantial impact on the quality of life of the patient. The illness is rather heterogeneous with different evolution among patients. A machine learning approach is followed in this paper to identify potential genes that are related to IBD. This is done by following a Monte Carlo simulation approach. In total, 23 different machine learning techniques were tested (in addition to a base level obtained using artificial neural networks). The best model identified 74 genes selected by the algorithm as being potentially involved in IBD. IBD seems to be a polygenic illness, in which environmental factors might play an important role. Following a machine learning approac

SUBMITTER: Alfonso Perez G 

PROVIDER: S-EPMC10383667 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature