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Clinicians' Guide to Artificial Intelligence in Colon Capsule Endoscopy-Technology Made Simple

DIAGNOSTICS (2023)

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Review Surgery

Convolution neural network for the diagnosis of wireless capsule endoscopy: a systematic review and meta-analysis

Kaiwen Qin et al.

Summary: The systematic review showed that CNN application in WCE demonstrated high sensitivity and specificity for detecting ulcers/erosions, GI bleeding, and polyps/cancer. This suggests that CNN has the potential to become a crucial assistant in the diagnosis of WCE.

SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES (2022)

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Letter Gastroenterology & Hepatology

Comment on Artificial intelligence in gastroenterology: A state-of-the-art review

Thomas Bjorsum-Meyer et al.

Summary: Colon capsule endoscopy (CCE) has become an equal diagnostic alternative to optical colonoscopy (OC) due to technical improvements and the impact of the coronavirus pandemic. CCE is now being introduced in clinical practice to relieve the burden on endoscopy units and move investigations to outpatient clinics. However, a limitation of CCE is its inability to differentiate between adenomatous polyps and hyperplastic polyps.

WORLD JOURNAL OF GASTROENTEROLOGY (2022)

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Article Medicine, General & Internal

Performance of a Deep Learning System for Automatic Diagnosis of Protruding Lesions in Colon Capsule Endoscopy

Miguel Mascarenhas et al.

Summary: This study aimed to develop an artificial intelligence algorithm using a convolutional neural network for automatic detection of colonic protruding lesions in CCE images. The results showed that the developed algorithm accurately detected protruding lesions, which may increase the diagnostic accuracy and acceptance of CCE for screening of colorectal neoplasia.

DIAGNOSTICS (2022)

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Review Medicine, General & Internal

Artificial Intelligence in Colon Capsule Endoscopy-A Systematic Review

Sarah Moen et al.

Summary: This article provides an overview of the literature on the use of artificial intelligence for reviewing colonic mucosa by colon capsule endoscopy and discusses the necessary actions for its clinical application. The results indicate that artificial intelligence models have promising sensitivity for bowel cleansing and the detection of polyps and colorectal neoplasia.

DIAGNOSTICS (2022)

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Article Gastroenterology & Hepatology

Automatic detection of colorectal neoplasia in wireless colon capsule endoscopic images using a deep convolutional neural network

Atsuo Yamada et al.

Summary: An AI system using deep learning was developed to automatically detect colorectal neoplasms in colon capsule endoscopy (CCE) images. The system showed good performance in terms of sensitivity, specificity, and accuracy after being trained and validated with around 16,000 tumor images.

ENDOSCOPY (2021)

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Article Gastroenterology & Hepatology

Artificial intelligence in small bowel capsule endoscopy - current status, challenges and future promise

Xavier Dray et al.

Summary: Neural network-based solutions are being developed to aid physicians in reviewing small-bowel capsule endoscopy, with computer-assisted detection being a critical step. While weakly supervised solutions have shown promising results, more video-level evaluations and prospective studies are needed in the future.

JOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY (2021)

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Article Gastroenterology & Hepatology

The impact of reader fatigue on the accuracy of capsule endoscopy interpretation

Sabina Beg et al.

Summary: Experienced readers showed decreased lesion detection after reading just one capsule study, while novice readers' accuracy was unaffected by the number of capsules read. Fatigue did not correlate with reading accuracy.

DIGESTIVE AND LIVER DISEASE (2021)

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Article Gastroenterology & Hepatology

Artificial intelligence and colon capsule endoscopy: development of an automated diagnostic system of protruding lesions in colon capsule endoscopy

M. M. Saraiva et al.

Summary: The deep learning algorithm developed in this study accurately detects protruding lesions with a sensitivity, specificity, positive predictive value, and negative predictive value of 90.7%, 92.6%, 79.2%, and 96.9% respectively. The application of AI technology to colon capsule endoscopy may improve its diagnostic accuracy and acceptance for colorectal neoplasia screening.

TECHNIQUES IN COLOPROCTOLOGY (2021)

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Review Statistics & Probability

Challenges and opportunities beyond structured data in analysis of electronic health records

Maryam Tayefi et al.

Summary: Electronic health records contain valuable information and analyzing unstructured data from clinical text and images is complex. Challenges include data quality, privacy issues, and explaining machine learning results. Potential solutions include developing synthetic data generation methods and advancing privacy-preserving techniques.

WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS (2021)

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Review Gastroenterology & Hepatology

Capsule endoscopy - Recent developments and future directions

Stefania Chetcuti Zammit et al.

Summary: Capsule endoscopy (CE) plays an important role in investigating upper and lower gastrointestinal diseases, especially in monitoring patients with varices and detecting upper gastrointestinal hemorrhage. Findings on CE can guide further management through device-assisted enteroscopy. Artificial intelligence within CE shows promising potential for improved diagnostic yield and shorter reading time, with future integration expected to minimize reporting time and human error.

EXPERT REVIEW OF GASTROENTEROLOGY & HEPATOLOGY (2021)

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Article Gastroenterology & Hepatology

Clinical usefulness of a deep learning-based system as the first screening on small-bowel capsule endoscopy reading

Tomonori Aoki et al.

DIGESTIVE ENDOSCOPY (2020)

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Article Radiology, Nuclear Medicine & Medical Imaging

Synthesizing images from multiple kernels using a deep convolutional neural network

Andrew D. Missert et al.

MEDICAL PHYSICS (2020)

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Review Medicine, General & Internal

Artificial intelligence in gastrointestinal endoscopy: general overview

Ahmad El Hajjar et al.

CHINESE MEDICAL JOURNAL (2020)

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Article Computer Science, Hardware & Architecture

Application of deep learning for autonomous detection and localization of colorectal polyps in wireless colon capsule endoscopy

Esmaeil S. Nadimi et al.

COMPUTERS & ELECTRICAL ENGINEERING (2020)

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Article Gastroenterology & Hepatology

Automatic detection and classification of protruding lesions in wireless capsule endoscopy images based on a deep convolutional neural network

Hiroaki Saito et al.

GASTROINTESTINAL ENDOSCOPY (2020)

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Review Gastroenterology & Hepatology

Deep learning for wireless capsule endoscopy: a systematic review and meta-analysis

Shelly Soffer et al.

GASTROINTESTINAL ENDOSCOPY (2020)

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Article Gastroenterology & Hepatology

Machine learning in GI endoscopy: practical guidance in how to interpret a novel field

Fons van der Sommen et al.

GUT (2020)

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Review Gastroenterology & Hepatology

Evolving role of artificial intelligence in gastrointestinal endoscopy

Gulshan Parasher et al.

WORLD JOURNAL OF GASTROENTEROLOGY (2020)

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Article Health Care Sciences & Services

A short guide for medical professionals in the era of artificial intelligence

Bertalan Mesko et al.

NPJ DIGITAL MEDICINE (2020)

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Article Biotechnology & Applied Microbiology

Architectures and accuracy of artificial neural network for disease classification from omics data

Hui Yu et al.

BMC GENOMICS (2019)

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Article Gastroenterology & Hepatology

Automatic detection of erosions and ulcerations in wireless capsule endoscopy images based on a deep convolutional neural network

Tomonori Aoki et al.

GASTROINTESTINAL ENDOSCOPY (2019)

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Article Gastroenterology & Hepatology

Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study

Pu Wang et al.

GUT (2019)

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Article Medicine, General & Internal

Key challenges for delivering clinical impact with artificial intelligence

Christopher J. Kelly et al.

BMC MEDICINE (2019)

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Review Ophthalmology

Artificial intelligence and deep learning in ophthalmology

Daniel Shu Wei Ting et al.

BRITISH JOURNAL OF OPHTHALMOLOGY (2019)

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Article Gastroenterology & Hepatology

Diagnostic outcomes of esophageal cancer by artificial intelligence using convolutional neural networks

Yoshimasa Horie et al.

GASTROINTESTINAL ENDOSCOPY (2019)

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Review Gastroenterology & Hepatology

Overview of Deep Learning in Gastrointestinal Endoscopy

Jun Ki Min et al.

GUT AND LIVER (2019)

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Article Gastroenterology & Hepatology

Development of a computed cleansing score to assess quality of bowel preparation in colon capsule endoscopy

Aymeric Becq et al.

ENDOSCOPY INTERNATIONAL OPEN (2018)

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Article Gastroenterology & Hepatology

Assessment of bowel cleansing quality in colon capsule endoscopy using machine learning: a pilot study

Maria Magdalena Buijs et al.

ENDOSCOPY INTERNATIONAL OPEN (2018)

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Article Medicine, General & Internal

Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer

Babak Ehteshami Bejnordi et al.

JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2017)

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Review Mathematical & Computational Biology

A review of automatic selection methods for machine learning algorithms and hyper-parameter values

Gang Luo

NETWORK MODELING AND ANALYSIS IN HEALTH INFORMATICS AND BIOINFORMATICS (2016)

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Article Cardiac & Cardiovascular Systems

Machine Learning in Medicine

Rahul C. Deo

CIRCULATION (2015)

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Article Gastroenterology & Hepatology

Detection of Lesions During Capsule Endoscopy: Physician Performance Is Disappointing

YuanPu Zheng et al.

AMERICAN JOURNAL OF GASTROENTEROLOGY (2012)

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Article Health Care Sciences & Services

Bleeding Detection in Wireless Capsule Endoscopy Based on Probabilistic Neural Network

Guobing Pan et al.

JOURNAL OF MEDICAL SYSTEMS (2011)

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Article Gastroenterology & Hepatology

ASGE guideline: guidelines for credentialing and granting privileges for capsule endoscopy

DO Faigel et al.

GASTROINTESTINAL ENDOSCOPY (2005)

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