Joel Troya
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View article: Implementing endoscopy video recording in routine clinical practice: Strategies from three tertiary care centers
Implementing endoscopy video recording in routine clinical practice: Strategies from three tertiary care centers Open
Endoscopy video recordings are valuable data for training and deploying artificial intelligence (AI) models. However, collecting these data is challenging and time-consuming, demanding new workflows and robust data management strategies. H…
View article: Efficient artificial intelligence-based assessment of the gastroesophageal valve with Hill classification through active learning
Efficient artificial intelligence-based assessment of the gastroesophageal valve with Hill classification through active learning Open
View article: The Role of Specialized Instruments for Advanced Endoscopic Resections in Gastrointestinal Disease
The Role of Specialized Instruments for Advanced Endoscopic Resections in Gastrointestinal Disease Open
Introduction: Advanced endoscopic therapy techniques have been developed and have created alternative treatment options to surgical therapy for several gastrointestinal diseases. This work will focus on new endoscopic tools for special ind…
View article: Direct comparison of multiple computer-aided polyp detection systems
Direct comparison of multiple computer-aided polyp detection systems Open
Background and study aims Artificial intelligence (AI)-based systems for computer-aided detection (CADe) of polyps receive regular updates and occasionally offer customizable detection thresholds, both of which impact their performance, bu…
View article: Preclinical Evaluation of a Microwave-Based Accessory Device for Colonoscopy in an In Vivo Porcine Model with Colorectal Polyps
Preclinical Evaluation of a Microwave-Based Accessory Device for Colonoscopy in an In Vivo Porcine Model with Colorectal Polyps Open
Background and Aims: Colonoscopy is currently the most effective way of detecting colorectal cancer and removing polyps, but it has some drawbacks and can miss up to 22% of polyps. Microwave imaging has the potential to provide a 360° view…
View article: Design and Development of a Flexible 3D-Printed Endoscopic Grasping Instrument
Design and Development of a Flexible 3D-Printed Endoscopic Grasping Instrument Open
(1) Background: Interventional endoscopic procedures are growing more popular, requiring innovative instruments and novel techniques. Three-dimensional printing has demonstrated great potential for the rapid development of prototypes that …
View article: Artificial intelligence-based polyp size measurement in gastrointestinal endoscopy using the auxiliary waterjet as a reference
Artificial intelligence-based polyp size measurement in gastrointestinal endoscopy using the auxiliary waterjet as a reference Open
Background Measurement of colorectal polyp size during endoscopy is mainly performed visually. In this work, we propose a novel polyp size measurement system (Poseidon) based on artificial intelligence (AI) using the auxiliary waterjet as …
View article: A Real-Time Polyp-Detection System with Clinical Application in Colonoscopy Using Deep Convolutional Neural Networks
A Real-Time Polyp-Detection System with Clinical Application in Colonoscopy Using Deep Convolutional Neural Networks Open
Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. The best method to prevent CRC is with a colonoscopy. During this procedure, the gastroenterologist searches for polyps. However, there is a potential risk of p…
View article: New Concept of External and Independent Next-to-the-Scope Intraluminal Grasping Device (EINTS)
New Concept of External and Independent Next-to-the-Scope Intraluminal Grasping Device (EINTS) Open
Procedurile endoscopice intervenţionale implică o serie de manevre complexe şi precise.Îmbunătăţirea funcţiei instrumentelor endoscopice pentru a obţine o tracţiune suplimentară s-a bazat pe experienţa chirurgicală.Această idee a apărut fo…
View article: A video based benchmark data set (ENDOTEST) to evaluate computer-aided polyp detection systems
A video based benchmark data set (ENDOTEST) to evaluate computer-aided polyp detection systems Open
Our benchmark ENDOTEST may be helpful for preclinical testing of new CADe devices. There seems to be a correlation between a shorter FDT with a higher sensitivity and a lower specificity for polyp detection.
View article: Fast machine learning annotation in the medical domain: a semi-automated video annotation tool for gastroenterologists
Fast machine learning annotation in the medical domain: a semi-automated video annotation tool for gastroenterologists Open
View article: Pilot study of a new freely available computer-aided polyp detection system in clinical practice
Pilot study of a new freely available computer-aided polyp detection system in clinical practice Open
Purpose Computer-aided polyp detection (CADe) systems for colonoscopy are already presented to increase adenoma detection rate (ADR) in randomized clinical trials. Those commercially available closed systems often do not allow for data col…
View article: Development and evaluation of a deep learning model to improve the usability of polyp detection systems during interventions
Development and evaluation of a deep learning model to improve the usability of polyp detection systems during interventions Open
Background The efficiency of artificial intelligence as computer‐aided detection (CADe) systems for colorectal polyps has been demonstrated in several randomized trials. However, CADe systems generate many distracting detections, especiall…
View article: The influence of computer-aided polyp detection systems on reaction time for polyp detection and eye gaze
The influence of computer-aided polyp detection systems on reaction time for polyp detection and eye gaze Open
Background Multiple computer-aided systems for polyp detection (CADe) have been introduced into clinical practice, with an unclear effect on examiner behavior. This study aimed to measure the influence of a CADe system on reaction time, mu…
View article: A Real-Time Polyp Detection System with Clinical Application in Colonoscopy Using Deep Convolutional Neural Networks
A Real-Time Polyp Detection System with Clinical Application in Colonoscopy Using Deep Convolutional Neural Networks Open
Background : Colorectal cancer (CRC) is still a leading cause of cancer-related deaths worldwide. The best method to prevent CRC is a colonoscopy. During this procedure, the colonoscopist searches for polyps. However, there is a potential …
View article: A video based benchmark data set (ENDOTEST) to evaluate computer-aided polyp detection systems
A video based benchmark data set (ENDOTEST) to evaluate computer-aided polyp detection systems Open
Computer-aided polyp detection (CADe) may become a standard for polyp detection during colonoscopy. Several systems are already commercially available. We report on a video-based benchmark technique for the first preclinical assessment of …
View article: Frame-by-Frame Analysis of a Commercially Available Artificial Intelligence Polyp Detection System in Full-Length Colonoscopies
Frame-by-Frame Analysis of a Commercially Available Artificial Intelligence Polyp Detection System in Full-Length Colonoscopies Open
Introduction: Computer-aided detection (CADe) helps increase colonoscopic polyp detection. However, little is known about other performance metrics like the number and duration of false-positive (FP) activations or how stable…
View article: Supplementary Material for: Frame-by-Frame Analysis of a Commercially Available Artificial Intelligence Polyp Detection System in Full-Length Colonoscopies
Supplementary Material for: Frame-by-Frame Analysis of a Commercially Available Artificial Intelligence Polyp Detection System in Full-Length Colonoscopies Open
Introduction: Computer-aided detection (CADe) helps increase colonoscopic polyp detection. However, little is known about other performance metrics like the number and duration of false-positive (FP) activations or how stable…
View article: Fast Machine Learning Annotation in the Medical Domain: A Semi-Automated Video Annotation Tool for Gastroenterologists
Fast Machine Learning Annotation in the Medical Domain: A Semi-Automated Video Annotation Tool for Gastroenterologists Open
Background: Machine learning, especially deep learning, is becoming more and more relevant in research and development in the medical domain. For all of the supervised deep learning applications, data is the most critical factor in securin…
View article: Current status and limitations of artificial intelligence in colonoscopy
Current status and limitations of artificial intelligence in colonoscopy Open
Background Artificial intelligence (AI) using deep learning methods for polyp detection (CADe) and characterization (CADx) is on the verge of clinical application. CADe already implied its potential use in randomized controlled trials. Fur…