AIMC Topic: Gastrointestinal Agents

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Identifying key clinical and biochemical predictors of treatment outcomes in inflammatory bowel disease: a real-world evidence study.

Scientific reports
Inflammatory bowel disease (IBD), including Crohn's disease and Ulcerative colitis, often shows variable responses to biological therapies. Identifying the most significant variables for predicting the response to these therapies could help prioritiz...

Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn's disease.

Annals of medicine
BACKGROUND: Crohn's disease (CD) is a chronic inflammatory bowel disease, with infliximab (IFX) commonly used for treatment. However, no clinically applicable model currently exists to predict the response of patients with CD to IFX therapy. Given th...

Development and validation of peripheral blood DNA methylation signatures to predict response to biological therapy in adults with Crohn's disease (EPIC-CD): an epigenome-wide association study.

The lancet. Gastroenterology & hepatology
BACKGROUND: Biological therapeutics are widely used in Crohn's disease, with evidence of efficacy from randomised trials and real-world experience. Primary non-response is a common, poorly understood problem. We aimed to assess blood methylation as a...

The reality of modeling irritable bowel syndrome: progress and challenges.

Expert opinion on drug discovery
INTRODUCTION: Irritable bowel syndrome (IBS) is a common gastrointestinal disorder that is often therapeutically challenging. While research has advanced our understanding of IBS pathophysiology, developing precise models to predict drug response and...

Predicting Response to Neuromodulators or Prokinetics in Patients With Suspected Gastroparesis Using Machine Learning: The "BMI, Infectious Prodrome, Delayed GES, and No Diabetes" Model.

Clinical and translational gastroenterology
INTRODUCTION: Pharmacologic therapies for symptoms of gastroparesis (GP) have limited efficacy, and it is difficult to predict which patients will respond. In this study, we implemented a machine learning model to predict the response to prokinetics ...

Artificial Intelligence-Enabled Stool Analysis for Lactulose Titration Assistance in Hepatic Encephalopathy Through a Smartphone Application.

The American journal of gastroenterology
INTRODUCTION: Management of hepatic encephalopathy relies on self-titration of lactulose. In this feasibility trial, we assess an artificial intelligence-enabled tool to guide lactulose use through a smartphone application.

Artificial Intelligence Evaluation of Stool Quality Guides Management of Hepatic Encephalopathy Using a Smartphone App.

The American journal of gastroenterology
Lactulose-based hepatic encephalopathy treatment requires bowel movements/day titration, which is improved with Bristol stool scale (BSS) incorporation. Dieta app evaluates artificial intelligence (AI)-based BSS (AI-BSS) with stool images. Initially,...

Identifying risk factors of anti-TNF induced skin lesions and other adverse events in paediatric patients with inflammatory bowel disease.

Journal of pediatric gastroenterology and nutrition
OBJECTIVES: While higher infliximab (IFX) trough concentrations (TCs) are associated with better outcomes in patients with inflammatory bowel disease (IBD), they could pose a risk for adverse events (AEs), including IFX-induced skin lesions. Therefor...