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Related Concept Videos

Irritable Bowel Syndrome I: Introduction01:17

Irritable Bowel Syndrome I: Introduction

360
Irritable Bowel Syndrome (IBS) is characterized by functional disturbances in the gastrointestinal system, presenting a cluster of symptoms without evident structural or biochemical abnormalities. It primarily affects the large intestine and may cause abdominal pain, bloating, excessive gas, diarrhea, constipation, or both.
IBS is a chronic condition that can persist over a long period or recur frequently.
The pathogenesis of IBS involves a complex interplay of the following factors:
Altered...
360
Irritable Bowel Syndrome II: Clinical Features and Diagnostic Evaluation01:30

Irritable Bowel Syndrome II: Clinical Features and Diagnostic Evaluation

232
Irritable Bowel Syndrome II: Clinical Features and Diagnostic Evaluation
Irritable Bowel Syndrome (IBS) is classified into subtypes based on the predominant bowel habits as determined by the Bristol Stool Form Scale (BSFS). The subtypes are:
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Anatomy of the Intestines01:23

Anatomy of the Intestines

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Although digestion of proteins, carbohydrates, and lipids may begin in the stomach, it is completed in the intestine. The absorption of nutrients, water, and electrolytes from food and drink also occurs in the intestine. The intestines can be divided into two structurally distinct organs—the small and large intestines.
Small Intestines
The small intestine is an ~7 meter-long tube with an inner diameter of just 2.5 cm. Since most nutrients are absorbed here, the inner lining of the...
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Chronic Bowel Disorders: Introduction01:17

Chronic Bowel Disorders: Introduction

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Chronic bowel diseases are a group of long-term conditions affecting the digestive tract, characterized by inflammation and damage to the gut lining. These conditions primarily include irritable bowel syndrome and inflammatory bowel disease.
Irritable Bowel Syndrome (IBS) is a common disorder affecting the gastrointestinal tract. The distinctive feature is recurrent abdominal pain associated with altered bowel movements, manifesting as constipation, diarrhea, or fluctuating between both. The...
536
Bacterial Flora of the Large Intestine01:29

Bacterial Flora of the Large Intestine

640
The gut microbiome is formed by a vast and diverse community of bacteria that colonizes our large intestine. These bacteria start residing in the gut from birth and continue diversifying throughout life, influenced by factors such as diet, lifestyle, and stress. The gut bacterial community also includes bacteria from food and those that enter the colon through the anus.
The normal gut flora of the colon plays a critical role in generating essential vitamins such as vitamins K, B5, and B7.
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Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy01:26

Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy

140
This lesson explores three gastrointestinal imaging techniques: radionuclide testing, colonic transit studies, and virtual colonoscopy.
Radionuclide Testing
Radionuclide testing is a sophisticated medical technique for assessing gastrointestinal motility. It focuses on gastric emptying and colonic transit time. Radioactive markers track the movement of food through the digestive system, providing insights into gastrointestinal disorders.
In gastric emptying studies, a meal's liquid and...
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Related Experiment Video

Updated: Sep 9, 2025

Perturbations of Circulating miRNAs in Irritable Bowel Syndrome Detected Using a Multiplexed High-throughput Gene Expression Platform
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Perturbations of Circulating miRNAs in Irritable Bowel Syndrome Detected Using a Multiplexed High-throughput Gene Expression Platform

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Deciphering Gut Microbiome Dynamics in Irritable Bowel Syndrome Using Deep Learning.

Faisal1, S R Mani Sekhar1, D S Anurag1

  • 1Department of Information Science and Engineering, M S Ramaiah Institute of Technology, Bangalore, India.

Neurogastroenterology and Motility
|September 5, 2025
PubMed
Summary
This summary is machine-generated.

Deep machine learning models accurately classify diseases using human gut microbiome data. A deep neural network achieved 92.79% accuracy, highlighting potential for improved diagnostics and health outcomes.

Keywords:
classificationdeep learningirritable bowel syndromemachine learningmicrobiome

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Area of Science:

  • Microbiome research
  • Computational biology
  • Machine learning in medicine

Background:

  • The human gut microbiome plays a crucial role in health and disease, influencing physiological processes and metabolic/immune functions.
  • Complex, high-dimensional microbiome data presents significant analytical challenges due to intricate microbial interactions and inter-individual variability.
  • Conditions like Irritable Bowel Syndrome (IBS) are linked to gut microbiome alterations, making it a key area for research.

Purpose of the Study:

  • To investigate the application of advanced machine learning techniques for analyzing complex human gut microbiome data.
  • To identify effective models for accurate disease classification based on microbiome profiles.
  • To explore novel diagnostic and therapeutic strategies leveraging microbiome insights.

Main Methods:

  • Implementation and evaluation of multiple machine learning models: XGBoost, RandomForest, Logistic Regression, LightGBM, and a Deep Neural Network (DNN).
  • Meticulous preprocessing of high-dimensional microbiome data to extract meaningful patterns.
  • Rigorous cross-validation on a comprehensive dataset to ensure model robustness and reliability in disease classification.

Main Results:

  • Comparative analysis of model performance in terms of accuracy, sensitivity, and specificity.
  • The Deep Neural Network (DNN) demonstrated superior performance due to its advanced pattern recognition capabilities.
  • Achieved a high classification accuracy of 92.79% using the DNN model.

Conclusions:

  • The study enhances understanding of the microbiome's impact on human health and disease.
  • Advanced deep machine learning models offer powerful tools for analyzing complex microbiome data.
  • This research paves the way for improved diagnostic methods and potential advancements in global health outcomes.