Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Assessment of the Rectum and Anus01:25

Assessment of the Rectum and Anus

296
Evaluating the rectum and anus plays a crucial role in conducting a thorough physical examination of the gastrointestinal system. Although it may be uncomfortable and often embarrassing for the patient, it holds immense diagnostic value, particularly in detecting gastrointestinal diseases and abnormalities. This guide will explain how to perform this assessment using inspection and palpation methods.
Rectal Inspection
Begin by inspecting the perianal and anal areas for color, texture, rashes,...
296
Endoscopic Procedures II: Colonoscopy01:25

Endoscopic Procedures II: Colonoscopy

145
The colon, or large intestine, is the final segment of the digestive system. Its primary functions include absorbing water and vitamins produced by gut bacteria and transforming waste from liquid to solid to form stool. In adults, the large intestine is approximately 5 feet long and consists of four main sections:
145
Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy01:26

Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy

120
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...
120

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Food for thought? The effects of the Healthy Primary School of the Future on children's educational outcomes.

PloS one·2026
Same author

Discrepancies in prescribed medications as reported by patients, general practitioners, and community pharmacists in older patients with polypharmacy in primary care.

BMC primary care·2026
Same author

Controlling Fecal Incontinence With a Novel Anal Device: A Randomized Clinical Trial.

JAMA network open·2026
Same author

Effect of Cigarette Type and Smoking Behavior on Urinary Metabolite Levels of Tobacco-Associated Toxicants.

Chemical research in toxicology·2026
Same author

Attitudes of patients and family members towards deferred and waived consent in ECPR research, an ancillary study of the INCEPTION trial.

Resuscitation plus·2026
Same author

Evaluating Performance of a Deep Learning-based Artificial Intelligence Model for Ovarian Tumor Classification Using a Multicenter CT Dataset.

Radiology. Imaging cancer·2026

Related Experiment Video

Updated: Jul 29, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

356

Automatic textual description of colorectal polyp features: explainable artificial intelligence.

Ayla Thijssen1,2, Ramon-Michel R Schreuder3, Roger Fonollà4

  • 1Maastricht University Medical Center, Division of Gastroenterology and Hepatology, Maastricht, Netherlands.

Endoscopy International Open
|May 19, 2023
PubMed
Summary
This summary is machine-generated.

Explainable artificial intelligence (AI) systems can automatically describe colorectal polyps (CRPs) using Blue Light Imaging (BLI) data. This technology aims to improve endoscopist understanding and trust in AI for better colorectal cancer diagnosis.

More Related Videos

Artificial Intelligence Approaches to Assessing Primary Cilia
08:58

Artificial Intelligence Approaches to Assessing Primary Cilia

Published on: May 1, 2021

3.6K
Flexible Colonoscopy in Mice to Evaluate the Severity of Colitis and Colorectal Tumors Using a Validated Endoscopic Scoring System
15:49

Flexible Colonoscopy in Mice to Evaluate the Severity of Colitis and Colorectal Tumors Using a Validated Endoscopic Scoring System

Published on: October 16, 2013

31.9K

Related Experiment Videos

Last Updated: Jul 29, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

356
Artificial Intelligence Approaches to Assessing Primary Cilia
08:58

Artificial Intelligence Approaches to Assessing Primary Cilia

Published on: May 1, 2021

3.6K
Flexible Colonoscopy in Mice to Evaluate the Severity of Colitis and Colorectal Tumors Using a Validated Endoscopic Scoring System
15:49

Flexible Colonoscopy in Mice to Evaluate the Severity of Colitis and Colorectal Tumors Using a Validated Endoscopic Scoring System

Published on: October 16, 2013

31.9K

Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Gastroenterology

Background:

  • Computer-aided diagnosis (CADx) systems show promise for improving colorectal polyp (CRP) optical diagnosis.
  • Integration of AI into clinical practice requires endoscopist understanding and trust in these systems.
  • Explainable AI (XAI) can enhance comprehension of AI diagnostic reasoning.

Purpose of the Study:

  • To develop an explainable AI CADx system capable of automatically generating textual descriptions of CRPs.
  • To assess the performance of the AI CADx system in describing CRP features using Blue Light Imaging (BLI) data.
  • To evaluate the potential of XAI to facilitate clinical integration and increase trust in AI diagnostic tools.

Main Methods:

  • Trained and tested an AI CADx system using textual descriptions based on the Blue Light Imaging (BLI) Adenoma Serrated International Classification (BASIC).
  • Utilized BLI images of 55 CRPs for CADx testing, with gold standard reference descriptions agreed upon by expert endoscopists.
  • Analyzed CADx performance by calculating agreement (Gwet's AC1) between generated and reference descriptions for various CRP features.

Main Results:

  • The AI CADx system successfully generated textual descriptions for CRP features.
  • High agreement was observed for surface descriptors (mucus, regularity, depression) and pit/vessel features.
  • Lower agreement was noted for CRP size and pits-distribution, indicating areas for improvement.
  • Gwet's AC1 values ranged from 0.167 (pits-distribution) to 0.957 (pits-type).

Conclusions:

  • Explainable AI CADx can automatically generate descriptive text for CRPs, aiding endoscopist comprehension.
  • The system demonstrated strong performance in describing surface characteristics and some internal features.
  • Further refinement is needed for size and pits-distribution descriptors to enhance overall diagnostic accuracy.
  • XAI facilitates trust and integration of AI tools into clinical endoscopy practice.