AIMC Topic: Esophageal Diseases

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The robot can break bars with the best of them: a novel approach to treating cricopharyngeal bars with myotomy.

Surgical endoscopy Sep 13, 2023
INTRODUCTION: Failure of the cricopharyngeus to relax results in oropharyngeal dysphagia, which over time results in hypertrophy and increased risk for aspiration. Open myotomy is one definitive treatment option, however there are several drawbacks a...
Retrospective Studies Female Aged Humans Deglutition Disorders Esophageal Diseases Myotomy Male Robotics Adult
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Improving the Classification Performance of Esophageal Disease on Small Dataset by Semi-supervised Efficient Contrastive Learning.

Journal of medical systems Nov 22, 2021
The classification of esophageal disease based on gastroscopic images is important in the clinical treatment, and is also helpful in providing patients with follow-up treatment plans and preventing lesion deterioration. In recent years, deep learning...
Esophageal Diseases Supervised Machine Learning Gastroscopy Humans
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Using machine-learning algorithms to identify patients at high risk of upper gastrointestinal lesions for endoscopy.

Journal of gastroenterology and hepatology May 10, 2021
BACKGROUND AND AIM: Endoscopic screening for early detection of upper gastrointestinal (UGI) lesions is important. However, population-based endoscopic screening is difficult to implement in populous countries. By identifying high-risk individuals fr...
Artificial Intelligence Machine Learning Algorithms Humans Male Middle Aged Risk Assessment Adult Stomach Neoplasms Female Esophageal Diseases Duodenal Diseases Mass Screening Endoscopy, Gastrointestinal Patient Selection China Logistic Models
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Endoscopic detection and differentiation of esophageal lesions using a deep neural network.

Gastrointestinal endoscopy Oct 1, 2019
BACKGROUND AND AIMS: Diagnosing esophageal squamous cell carcinoma (SCC) depends on individual physician expertise and may be subject to interobserver variability. Therefore, we developed a computerized image-analysis system to detect and differentia...
Narrow Band Imaging Observer Variation Aged, 80 and over Precancerous Conditions Adult Esophageal Squamous Cell Carcinoma Neoplasm Invasiveness Aged Esophageal Diseases Esophagus Deep Learning Optical Imaging Male Esophageal Neoplasms Sensitivity and Specificity Image Processing, Computer-Assisted Neural Networks, Computer Middle Aged Humans Female Reproducibility of Results
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The IDEAL prospective development study format for reporting surgical innovations. An illustrative case study of robotic oesophagectomy.

International journal of surgery (London, England) Apr 17, 2015
BACKGROUND: The early development of innovative surgical procedures is usually reported as retrospective case series, wasting opportunities to provide useful information and introducing bias. We present a report of an innovative procedure in developm...
Robotics Esophagectomy Esophageal Diseases Middle Aged Prospective Studies Operative Time Aged, 80 and over Reproducibility of Results Aged Adult Retrospective Studies Humans Female Male
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Artificial intelligence-assisted endoscopic ultrasound diagnosis of esophageal subepithelial lesions.

Surgical endoscopy Jun 1, 2025
BACKGROUND: Endoscopic ultrasound (EUS) is one of the most accurate methods for determining the originating layer of subepithelial lesions (SELs). However, the accuracy is greatly influenced by the expertise and proficiency of the endoscopist. In thi...
Esophageal Diseases Male Female Humans Middle Aged Esophageal Neoplasms Esophagus Aged Artificial Intelligence Endosonography Adult
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[Applications of Machine Learning for Radiation Therapy].

Igaku butsuri : Nihon Igaku Butsuri Gakkai kikanshi = Japanese journal of medical physics : an official journal of Japan Society of Medical Physics Jan 1, 2016
Radiation therapy has been highly advanced as image guided radiation therapy (IGRT) by making advantage of image engineering technologies. Recently, novel frameworks based on image engineering technologies as well as machine learning technologies hav...
Humans Machine Learning Radiation Injuries Technology, Radiologic Radiotherapy Esophageal Diseases
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