AIMC Topic: Irritable Bowel Syndrome

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Irritable bowel syndrome-specific volatile organic compounds in faecal headspace do not associate with classical symptom-based subtypes.

Journal of breath research
Irritable bowel syndrome (IBS), a disorder of gut-brain interaction, is diagnosed using symptom-based Rome criteria. These criteria classify IBS patients into four subtypes in accordance to their stool patterns. However, whether this subtyping approa...

Artificial Intelligence Methods for the Differential Diagnosis of Irritable Bowel Syndrome and Inflammatory Bowel Disease: A Systematic Review.

Journal of gastrointestinal and liver diseases : JGLD
BACKGROUND AND AIMS: Differential diagnosis between irritable bowel syndrome (IBS) and inflammatory bowel disease (IBD) represents a major challenge in modern gastroenterology due to overlapping symptoms, limitations of traditional diagnostic methods...

Multi-omics analysis reveal clinical-gut-brain interactions in female ibs patients with adverse childhood experiences.

Biology of sex differences
BACKGROUND: The brain-gut system, which involves bidirectional communication between the central nervous system and the gut, plays a central role in stress responses. Its dysregulation is implicated in irritable bowel syndrome (IBS), a stress-sensiti...

Management of Irritable Bowel Syndrome: The Role of Digital Health Technologies.

Journal of gastrointestinal and liver diseases : JGLD
Functional Gastrointestinal Disorders (FGIDs), including conditions such as irritable bowel syndrome (IBS) and functional dyspepsia, affect millions worldwide, significantly impairing quality of life and increasing healthcare utilization. These disor...

Multi-kingdom microbiota analysis reveals bacteria-viral interplay in IBS with depression and anxiety.

NPJ biofilms and microbiomes
Irritable Bowel Syndrome (IBS) is a common gastrointestinal disorder frequently accompanied by psychological symptoms. Bacterial microbiota plays a critical role in mediating local and systemic immunity, and alterations in these microbial communities...

Learning a deep language model for microbiomes: The power of large scale unlabeled microbiome data.

PLoS computational biology
We use open source human gut microbiome data to learn a microbial "language" model by adapting techniques from Natural Language Processing (NLP). Our microbial "language" model is trained in a self-supervised fashion (i.e., without additional externa...

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...

Classification of Irritable Bowel Syndrome Using Brain Functional Connectivity Strength and Machine Learning.

Neurogastroenterology and motility
BACKGROUND: Irritable Bowel Syndrome (IBS) is a prevalent condition characterized by dysregulated brain-gut interactions. Despite its widespread impact, the brain mechanism of IBS remains incompletely understood, and there is a lack of objective diag...

Decoding IBS: a machine learning approach to psychological distress and gut-brain interaction.

BMC gastroenterology
PURPOSE: Irritable bowel syndrome (IBS) is a diagnosis defined by gastrointestinal (GI) symptoms like abdominal pain and changes associated with defecation. The condition is classified as a disorder of the gut-brain interaction (DGBI), and patients w...

Altered resting-state functional connectivity and effective connectivity of the habenula in irritable bowel syndrome: A cross-sectional and machine learning study.

Human brain mapping
Irritable bowel syndrome (IBS) is a disorder involving dysfunctional brain-gut interactions characterized by chronic recurrent abdominal pain, altered bowel habits, and negative emotion. Previous studies have linked the habenula to the pathophysiolog...