On the public citation graph

Automatic detection of different types of small-bowel lesions on capsule endoscopy images using a newly developed deep convolutional neural network

https://doi.org/10.1055/a-1167-8157
0 signed · 56 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-46448-0_2openalex-snapshot
SSD: Single Shot MultiBox Detector
inferredcites →https://doi.org/10.1016/j.compbiomed.2017.03.031openalex-snapshot
Quantitative analysis of patients with celiac disease by video capsule endoscopy: A deep learning method
inferredcites →https://doi.org/10.1016/j.gie.2018.10.027openalex-snapshot
Automatic detection of erosions and ulcerations in wireless capsule endoscopy images based on a deep convolutional neural network
inferredcites →https://doi.org/10.1016/s0016-5107(04)00003-3openalex-snapshot
Simethicone for small bowel preparation for capsule endoscopy: a systematic, single-blinded, controlled study
inferredcites →https://doi.org/10.1038/35013140openalex-snapshot
Wireless capsule endoscopy
inferredcites →https://doi.org/10.1053/j.gastro.2019.06.025openalex-snapshot
Gastroenterologist-Level Identification of Small-Bowel Diseases and Normal Variants by Capsule Endoscopy Using a Deep-Learning Model
inferredcites →https://doi.org/10.1109/tpami.2018.2858826openalex-snapshot
Focal Loss for Dense Object Detection
inferredcites →https://doi.org/10.1111/den.12922openalex-snapshot
Associations between drugs and small‐bowel mucosal bleeding: Multicenter capsule‐endoscopy study
inferredcites →https://doi.org/10.1111/den.13507openalex-snapshot
Artificial intelligence using a convolutional neural network for automatic detection of small‐bowel angioectasia in capsule endoscopy images
inferredcites →https://doi.org/10.2307/2531595openalex-snapshot
Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4180735openalex-extracted
Diagnostic Accuracy of Artificial Intelligence for Detecting Gastroenterological Pathologies: A Systematic Review and Meta-Analysis
inferred← citeshttps://doi.org/10.1002/deo2.258openalex-snapshot
Small bowel capsule endoscopy examination and open access database with artificial intelligence: The SEE‐artificial intelligence project
inferred← citeshttps://doi.org/10.1002/mog2.91openalex-snapshot
The application of the combination between artificial intelligence and endoscopy in gastrointestinal tumors
inferred← citeshttps://doi.org/10.1007/978-3-031-64719-2_57openalex-snapshot
Artificial Intelligence
inferred← citeshttps://doi.org/10.1007/s00464-021-08689-3openalex-snapshot
Convolution neural network for the diagnosis of wireless capsule endoscopy: a systematic review and meta-analysis
inferred← citeshttps://doi.org/10.1007/s10278-024-01096-9openalex-snapshot
Cascade-EC Network: Recognition of Gastrointestinal Multiple Lesions Based on EfficientNet and CA_stm_Retinanet
inferred← citeshttps://doi.org/10.1007/s10620-021-07086-zopenalex-snapshot
Artificial Intelligence in Endoscopy
inferred← citeshttps://doi.org/10.1007/s11517-025-03380-4openalex-snapshot
Deep ensemble framework with Bayesian optimization for multi-lesion recognition in capsule endoscopy images
inferred← citeshttps://doi.org/10.1016/j.bpg.2021.101742openalex-snapshot
Small Bowel Capsule Endoscopy and artificial intelligence: First or second reader?
inferred← citeshttps://doi.org/10.1016/j.gie.2020.08.014openalex-snapshot
The exceptional performance of deep learning for capsule endoscopy: Will such quality be maintained in clinical scenarios?
inferred← citeshttps://doi.org/10.1016/j.gie.2023.07.024openalex-snapshot
Disease surveillance evaluation of primary small-bowel follicular lymphoma using capsule endoscopy images based on a deep convolutional neural network (with video)
inferred← citeshttps://doi.org/10.1016/j.gie.2023.11.059openalex-snapshot
Deep learning–based lesion detection and severity grading of small-bowel Crohn’s disease ulcers on double-balloon endoscopy images
inferred← citeshttps://doi.org/10.1016/j.giec.2024.07.002openalex-snapshot
Capsule Endoscopy in Inflammatory Bowel Disease
inferred← citeshttps://doi.org/10.1016/j.giec.2024.12.001openalex-snapshot
The Use of Artificial Intelligence for Endoscopic Evaluation of the Small Bowel
inferred← citeshttps://doi.org/10.1016/j.gtc.2026.08.004openalex-snapshot
Artificial Intelligence for Capsule Endoscopy
inferred← citeshttps://doi.org/10.1055/a-1388-6735openalex-snapshot
Real-time deep learning-based colorectal polyp localization on clinical video footage achievable with a wide array of hardware configurations
inferred← citeshttps://doi.org/10.1055/a-1881-4209openalex-snapshot
Artificial intelligence-based diagnosis of abnormalities in small-bowel capsule endoscopy
inferred← citeshttps://doi.org/10.1055/a-2236-7849openalex-snapshot
Deep learning and capsule endoscopy: Automatic multi-brand and multi-device panendoscopic detection of vascular lesions
inferred← citeshttps://doi.org/10.1055/s-0044-1800916openalex-snapshot
Capsule Endoscopy Technology: A New Era in Digestive Tract Examination
inferred← citeshttps://doi.org/10.1063/5.0054161openalex-snapshot
Multiple abnormality classification in wireless capsule endoscopy images based on EfficientNet using attention mechanism
inferred← citeshttps://doi.org/10.1080/17474124.2022.2020646openalex-snapshot
Application and prospect of artificial intelligence in digestive endoscopy
inferred← citeshttps://doi.org/10.1097/mog.0000000000000827openalex-snapshot
Artificial intelligence within the small bowel: are we lagging behind?
inferred← citeshttps://doi.org/10.1111/den.13888openalex-snapshot
Artificial intelligence and its impact on quality improvement in upper and lower gastrointestinal endoscopy
inferred← citeshttps://doi.org/10.1111/jgh.15341openalex-snapshot
Artificial intelligence in small bowel capsule endoscopy ‐ current status, challenges and future promise
inferred← citeshttps://doi.org/10.1111/jgh.16369openalex-snapshot
Comparison of clinical utility of deep learning‐based systems for small‐bowel capsule endoscopy reading
inferred← citeshttps://doi.org/10.11641/pde.100.1_27openalex-snapshot
Automatic detection of small-bowel lesions from capsule endoscopy images using a deep convolutional neural network: A systematic review and meta-analysis
inferred← citeshttps://doi.org/10.1186/s12876-023-03067-wopenalex-snapshot
A newly developed deep learning-based system for automatic detection and classification of small bowel lesions during double-balloon enteroscopy examination
inferred← citeshttps://doi.org/10.18705/3034-7270-2025-1-2-8-20openalex-snapshot
Artificial intelligence technologies in digestive system endoscopy: the state of the problem and prospects (literature review)
inferred← citeshttps://doi.org/10.20517/2574-1225.2023.102openalex-snapshot
Artificial intelligence in capsule endoscopy: development status and future expectations
inferred← citeshttps://doi.org/10.20524/aog.2021.0653openalex-snapshot
Artificial intelligence and capsule endoscopy: automatic detection of vascular lesions using a convolutional neural network
inferred← citeshttps://doi.org/10.3389/fmed.2022.1018937openalex-snapshot
Diagnostic accuracy of artificial intelligence for detecting gastrointestinal luminal pathologies: A systematic review and meta-analysis
inferred← citeshttps://doi.org/10.3390/biomedicines11030942openalex-snapshot
Improved Object Detection Artificial Intelligence Using the Revised RetinaNet Model for the Automatic Detection of Ulcerations, Vascular Lesions, and Tumors in Wireless Capsule Endoscopy
inferred← citeshttps://doi.org/10.3390/diagnostics11071183openalex-snapshot
A Current and Newly Proposed Artificial Intelligence Algorithm for Reading Small Bowel Capsule Endoscopy
inferred← citeshttps://doi.org/10.3390/diagnostics11112122openalex-snapshot
Image-Enhanced Capsule Endoscopy Improves the Identification of Small Intestinal Lesions
inferred← citeshttps://doi.org/10.3390/diagnostics13081389openalex-snapshot
Automatic Classification of GI Organs in Wireless Capsule Endoscopy Using a No-Code Platform-Based Deep Learning Model
inferred← citeshttps://doi.org/10.3390/diagnostics14030291openalex-snapshot
From Data to Insights: How Is AI Revolutionizing Small-Bowel Endoscopy?
inferred← citeshttps://doi.org/10.3390/jcm11133682openalex-snapshot
Development of a Deep-Learning Algorithm for Small Bowel-Lesion Detection and a Study of the Improvement in the False-Positive Rate
inferred← citeshttps://doi.org/10.37126/aige.v2.i4.179openalex-snapshot
Artificial intelligence as a means to improve recognition of gastrointestinal angiodysplasia in video capsule endoscopy
inferred← citeshttps://doi.org/10.3748/wjg.v27.i25.3734openalex-snapshot
Artificial intelligence in small intestinal diseases: Application and prospects
inferred← citeshttps://doi.org/10.3748/wjg.v27.i37.6191openalex-snapshot
Challenges and opportunities in the application of artificial intelligence in gastroenterology and hepatology
inferred← citeshttps://doi.org/10.3748/wjg.v27.i38.6476openalex-snapshot
Deep learning vs conventional learning algorithms for clinical prediction in Crohn's disease: A proof-of-concept study
inferred← citeshttps://doi.org/10.3748/wjg.v27.i40.6794openalex-snapshot
Artificial intelligence in gastroenterology: A state-of-the-art review
inferred← citeshttps://doi.org/10.3748/wjg.v31.i27.106819openalex-snapshot
Deep learning-based localization and lesion detection in capsule endoscopy for patients with suspected small-bowel bleeding
inferred← citeshttps://doi.org/10.5009/gnl220507openalex-snapshot
Capsule Endoscopy in Inflammatory Bowel Disease: Panenteric Capsule Endoscopy and Application of Artificial Intelligence
inferred← citeshttps://doi.org/10.5946/ce.2022.113openalex-snapshot
Recent developments in small bowel endoscopy: the “black box” is now open!
inferred← citeshttps://doi.org/10.6084/m9.figshare.24934462openalex-snapshot
Additional file 1 of A newly developed deep learning-based system for automatic detection and classification of small bowel lesions during double-balloon enteroscopy examination
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.