Article

Real-World Colonoscopy Video Integration to Improve Artificial Intelligence Polyp Detection Performance and Reduce Manual Annotation Labor

2025-03-13

Abstract excerpt

<h4>Background: </h4> /Objectives: Artificial intelligence (AI) integration in colon polyp detection often exhibits high sensitivity but notably low specificity in real-world settings, primarily due to reliance on publicly available datasets alone. To address this limitation, we proposed a semi-automatic annotation method using real colonoscopy videos to enhance AI model performance and reduce manual labeling labo...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 4c8b6a00-81c4-5a28-8bb4-2335c80699df
DOI: 10.20944/preprints202503.0938.v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Real-World Colonoscopy Video Integration to Improve Artificial Intelligence Polyp Detection Performance and Reduce Manual Annotation LaborDOI 10.20944/preprints202503.0938.v1Read

Using Synthetic and Pseudosynthetic Data to Enhance Polyp Detection in Future AI-Assisted Endoscopy Frameworks. Is it the Right Time?Semantic proximity Read

Biomimetic Transfer Learning-based Complex Gastrointestinal Polyp ClassificationSemantic proximity Read

Performance of a deep learning system for automatic diagnosis of protruding lesions in colon capsule endoscopy: a multicentric studySemantic proximity Read

Accurate Diagnosis of Colorectal Cancer Based on Histopathology Images Using Artificial IntelligenceSemantic proximity Read

Screening of normal endoscopic large bowel biopsies with artificial intelligence: a retrospective studySemantic proximity Read

An Adaptive Foundation Model with Evidence-based Clinical Reasoning for GastroenterologySemantic proximity Read

Predicting Generalization of AI Colonoscopy Models to Unseen DataSemantic proximity Read

Enhancing Medical Image Segmentation through Negative Sample Integration: A Study on Kvasir-SEG and Augmented DatasetsSemantic proximity Read

Computer-Aided Diagnosis of Serrated Colorectal Lesions Using Non-Magnified White Light Endoscopic ImagesSemantic proximity Read

AI based pre-screening of large bowel cancer via weakly supervised learning of colorectal biopsy histology imagesSemantic proximity Read

Accurate recognition of colorectal cancer with semi-supervised deep learning on pathological imagesSemantic proximity Read

Whole-Case Artificial Intelligence for Diagnostic Escalation in Endoscopically Suspected Borrmann Type IV Gastric CancerSemantic proximity Read