AIMC Topic: Gastroesophageal Reflux
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Learning curves and procedural times in Senhance®-robotic assisted fundoplication: results from 237 consecutive patients undergoing robotic fundoplication in a single center as part of the European TRUST Robotic Surgery Registry Study.
Surgical endoscopy
Sep 5, 2023
BACKGROUND: Gastroesophageal reflux disease requiring an operative solution is common. Minimally invasive surgery to generate an anti-reflux barrier at the distal esophagus following the principle of the "floppy Nissen" technique has become the gold ...
Using deep learning and explainable artificial intelligence to assess the severity of gastroesophageal reflux disease according to the Los Angeles Classification System.
Scandinavian journal of gastroenterology
Jan 9, 2023
OBJECTIVES: Gastroesophageal reflux disease (GERD) is a complex disease with a high worldwide prevalence. The Los Angeles classification (LA-grade) system is meaningful for assessing the endoscopic severity of GERD. Deep learning (DL) methods have be...
Robotic single port anti-reflux surgery: Initial worldwide experience of two cases with a novel surgical approach to treat gastroesophageal reflux disease.
The international journal of medical robotics + computer assisted surgery : MRCAS
Sep 5, 2022
INTRODUCTION: To date, no anti-reflux operations have been reported with the new da Vinci Single-Port (single port (SP)) robotic platform. We aimed to describe this novel surgical approach and evaluate its safety and feasibility.
Robotic Transgastric Reconstruction of the Double Lumen Esophagus.
Innovations (Philadelphia, Pa.)
Jun 30, 2022
Double lumen esophagus is an extremely rare condition, developing in most cases as a complication of antireflux procedures or gastroesophageal reflux itself secondary to the severe inflammatory process in and around the lower esophagus. We describe a...
Systematic review with meta-analysis: artificial intelligence in the diagnosis of oesophageal diseases.
Alimentary pharmacology & therapeutics
Jan 30, 2022
BACKGROUND: Artificial intelligence (AI) has recently been applied to endoscopy and questionnaires for the evaluation of oesophageal diseases (ODs).
Association of Gastroesophageal Reflux Disease with Preterm Birth: Machine Learning Analysis.
Journal of Korean medical science
Nov 8, 2021
BACKGROUND: This study used machine learning and population data for testing the associations of preterm birth with gastroesophageal reflux disease (GERD) and periodontitis.
Robot-assisted Valvuloplastic Esophagogastrostomy by Double-flap Technique Using a Knifeless Linear Stapler After Proximal Gastrectomy.
Surgical laparoscopy, endoscopy & percutaneous techniques
Sep 17, 2021
After proximal gastrectomy, valvuloplastic esophagogastrostomy by double-flap technique could be the ideal reconstruction to prevent gastroesophageal reflux. However, it is demanding procedure in laparoscopic surgery. In this video, we demonstrate a ...
A Deep Learning Model for Classification of Endoscopic Gastroesophageal Reflux Disease.
International journal of environmental research and public health
Mar 2, 2021
Gastroesophageal reflux disease (GERD) is a common disease with high prevalence, and its endoscopic severity can be evaluated using the Los Angeles classification (LA grade). This paper proposes a deep learning model (i.e., GERD-VGGNet) that employs ...
Short-term outcome after robot-assisted hiatal hernia and anti-reflux surgery-is there a benefit for the patient?
Langenbeck's archives of surgery
Jan 6, 2021
PURPOSE: The robotic system was introduced to overcome the technical limitations of conventional laparoscopy. For complex oncological operations, it appears to offer further advantages. With regard to hiatal hernia repair, its role has yet to be dete...
Artificial intelligence automates and augments baseline impedance measurements from pH-impedance studies in gastroesophageal reflux disease.
Journal of gastroenterology
Nov 5, 2020
BACKGROUND: Artificial intelligence (AI) has potential to streamline interpretation of pH-impedance studies. In this exploratory observational cohort study, we determined feasibility of automated AI extraction of baseline impedance (AIBI) and evaluat...
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