AIMC Topic: Gastrointestinal Agents
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The reality of modeling irritable bowel syndrome: progress and challenges.
Expert opinion on drug discovery
Mar 31, 2025
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
Sep 1, 2024
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 ...
Machine Learning-Based Prediction of Pediatric Ulcerative Colitis Treatment Response Using Diagnostic Histopathology.
Gastroenterology
Feb 2, 2024
Artificial Intelligence-Enabled Stool Analysis for Lactulose Titration Assistance in Hepatic Encephalopathy Through a Smartphone Application.
The American journal of gastroenterology
Jan 19, 2024
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
Dec 28, 2023
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,...
Anti-infliximab antibodies and low infliximab levels correlate with drug discontinuation in pediatric inflammatory bowel disease.
Journal of pediatric gastroenterology and nutrition
Dec 27, 2023
BACKGROUND: Infliximab (IFX) use is limited by loss of response often due to the development of anti-IFX antibodies and low drug levels.
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
Dec 10, 2023
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...
Effectiveness of strategies to suppress antibodies to infliximab in pediatric inflammatory bowel disease.
Journal of pediatric gastroenterology and nutrition
Dec 5, 2023
OBJECTIVES: Antibodies to infliximab (ATIs) are associated with loss of response in children with inflammatory bowel disease (IBD). We aimed to describe the effectiveness of strategies for treatment modification following ATI development in pediatric...
Artificial Neural Network Analysis-Based Immune-Related Signatures of Primary Non-Response to Infliximab in Patients With Ulcerative Colitis.
Frontiers in immunology
Dec 21, 2021
Infliximab (IFX) is an effective medication for ulcerative colitis (UC) patients. However, one-third of UC patients show primary non-response (PNR) to IFX. Our study analyzed three Gene Expression Omnibus (GEO) datasets and used the RobustRankAggreg ...
Machine learning using clinical data at baseline predicts the efficacy of vedolizumab at week 22 in patients with ulcerative colitis.
Scientific reports
Aug 12, 2021
Predicting the response of patients with ulcerative colitis (UC) to a biologic such as vedolizumab (VDZ) before administration is an unmet need for optimizing individual patient treatment. We hypothesized that the machine-learning approach with daily...
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