ReviewDiagnostics (Basel, Switzerland)2021
Artificial Intelligence in Capsule Endoscopy: A Practical Guide to Its Past and Future Challenges.
Review in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence-Assisted Capsule Endoscopy Versus Conventional Capsule Endoscopy for Detection of Small Bowel Lesions: A Systematic Review and Meta-Analysis.Journal of gastroenterology and hepatology · 2025Pooled it
- Expected Values of Artificial Intelligence in Colon Capsule Endoscopy: Artificial Intelligence in Capsule Endoscopy Consortium Position Statement.Endoscopy international open · 2026Article
- Artificial Intelligence in Thoracic Surgery: Transforming Diagnostics, Treatment, and Patient Outcomes.Diagnostics (Basel, Switzerland) · 2025Review
- Classification of pediatric video capsule endoscopy images for small bowel abnormalities using deep learning models.World journal of gastroenterology · 2025Article
- Software as a Medical Device (SaMD) in Digestive Healthcare: Regulatory Challenges and Ethical Implications.Diagnostics (Basel, Switzerland) · 2024Review
- Deep Learning-Based Real-Time Organ Localization and Transit Time Estimation in Wireless Capsule Endoscopy.Biomedicines · 2024Article
- Automatic detection of small bowel lesions with different bleeding risks based on deep learning models.World journal of gastroenterology · 2024Article
- Smart Endoscopy Is Greener Endoscopy: Leveraging Artificial Intelligence and Blockchain Technologies to Drive Sustainability in Digestive Health Care.Diagnostics (Basel, Switzerland) · 2023Review
- AI-Driven Colon Cleansing Evaluation in Capsule Endoscopy: A Deep Learning Approach.Diagnostics (Basel, Switzerland) · 2023Article
- Video Analysis of Small Bowel Capsule Endoscopy Using a Transformer Network.Diagnostics (Basel, Switzerland) · 2023Article
- The Advent of Domain Adaptation into Artificial Intelligence for Gastrointestinal Endoscopy and Medical Imaging.Diagnostics (Basel, Switzerland) · 2023Review
- Design of a Convolutional Neural Network as a Deep Learning Tool for the Automatic Classification of Small-Bowel Cleansing in Capsule Endoscopy.Medicina (Kaunas, Lithuania) · 2023Article
- The Promise of Artificial Intelligence in Digestive Healthcare and the Bioethics Challenges It Presents.Medicina (Kaunas, Lithuania) · 2023Review
- Automatic Classification of GI Organs in Wireless Capsule Endoscopy Using a No-Code Platform-Based Deep Learning Model.Diagnostics (Basel, Switzerland) · 2023Article
- Revealing the Boundaries of Selected Gastro-Intestinal (GI) Organs by Implementing CNNs in Endoscopic Capsule Images.Diagnostics (Basel, Switzerland) · 2023Article
- The Role of Artificial Intelligence in Monitoring Inflammatory Bowel Disease-The Future Is Now.Diagnostics (Basel, Switzerland) · 2023Review
- A systematic review on diagnosis and treatment of gastrointestinal diseases by magnetically controlled capsule endoscopy and artificial intelligence.Therapeutic advances in gastroenterology · 2023Review
- Small Bowel Detection for Wireless Capsule Endoscopy Using Convolutional Neural Networks with Temporal Filtering.Diagnostics (Basel, Switzerland) · 2022Article
- Review
- The global research of artificial intelligence on inflammatory bowel disease: A bibliometric analysis.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Artificial intelligence (AI) has revolutionized the medical diagnostic process of various diseases. Since the manual reading of capsule endoscopy videos is a time-intensive, error-prone process, computerized algorithms have been introduced to automate this process. Over the past decade, the evolution of convolutional neural network (CNN) enabled AI to detect multiple lesions simultaneously with increasing accuracy and sensitivity. Difficulty in validating CNN performance and unique characteristics of capsule endoscopy images make computer-aided reading systems in capsule endoscopy still on a preclinical level. Although AI technology can be used as an auxiliary second observer in capsule endoscopy, it is expected that in the near future, it will effectively reduce the reading time and ultimately become an independent, integrated reading system.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.