Inflammatory bowel disease (IBD) is a chronic, incurable disease involving the
gastrointestinal tract. It is characterized by complex, unclear pathogenesis, increased …

Abstract Background and Aims There is increasing interest in machine learning-based
prediction models in inflammatory bowel diseases [IBD]. We synthesised and critically …

Purpose Inflammatory bowel disease (IBD) is difficult to diagnose and classify. The purpose
of this study is to establish an artificial intelligence model based on fecal multi-omics data for …

This study aimed to explore the effectiveness of predicting disease activity in patients with
inflammatory bowel disease (IBD), using machine learning (ML) models. A retrospective …

The intestinal microbiota is a crucial environmental factor in the development of
inflammatory bowel disease (IBD). The abundance of Faecalibacterium prausnitzii is …

Objective Peripheral blood routine parameters (PBRPs) are simple and easily acquired
markers to identify ulcerative colitis (UC) and Crohn's disease (CD) and reveal the severity …

Research of inflammatory bowel disease (IBD) has identified numerous molecular players
involved in the disease development. Even so, the understanding of IBD is incomplete, while …

Background Improvement of patient quality of life is the ultimate goal of biomedical research,
particularly when dealing with complex, chronic and debilitating conditions such as …

Background Inflammatory bowel disease (IBD) is a gastrointestinal chronic disease with an
unpredictable disease course. Computational methods such as machine learning (ML) have …

Background Previous studies have demonstrated that serological markers can assist in
diagnosing inflammatory bowel disease (IBD). In this study, we aim to build a diagnostic tool …