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Endoscopy

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Use of Endoscopic Images in the Prediction of Submucosal Invasion of Gastric Neoplasms: Automated Deep Learning Model Development and Usability Study.

Journal of medical Internet research
BACKGROUND: In a previous study, we examined the use of deep learning models to classify the invasion depth (mucosa-confined versus submucosa-invaded) of gastric neoplasms using endoscopic images. The external test accuracy reached 77.3%. However, mo...

Automatic tip detection of surgical instruments in biportal endoscopic spine surgery.

Computers in biology and medicine
BACKGROUND: Recent advances in robotics and deep learning can be used in endoscopic surgeries and can provide numerous advantages by freeing one of the surgeon's hands. This study aims to automatically detect the tip of the instrument, localize a poi...

Ability of artificial intelligence to detect T1 esophageal squamous cell carcinoma from endoscopic videos and the effects of real-time assistance.

Scientific reports
Diagnosis using artificial intelligence (AI) with deep learning could be useful in endoscopic examinations. We investigated the ability of AI to detect superficial esophageal squamous cell carcinoma (ESCC) from esophagogastroduodenoscopy (EGD) videos...

Application of artificial intelligence using a convolutional neural network for detecting cholesteatoma in endoscopic enhanced images.

Auris, nasus, larynx
OBJECTIVE: We examined whether artificial intelligence (AI) used with the novel digital image enhancement system modalities (CLARA+CHROMA, SPECTRA A, and SPECTRA B) could distinguish the cholesteatoma matrix, cholesteatoma debris, and normal middle e...

A Deep Learning Model for Classification of Endoscopic Gastroesophageal Reflux Disease.

International journal of environmental research and public health
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 ...

Colorectal polyp characterization with standard endoscopy: Will Artificial Intelligence succeed where human eyes failed?

Best practice & research. Clinical gastroenterology
The American Society for Gastrointestinal Endoscopy (ASGE) has proposed the "resect-and-discard" and "diagnose-and-leave" strategies for diminutive colorectal polyps to reduce the costs of unnecessary polyp resection and pathology evaluation. However...

Overcoming barriers to implementation of artificial intelligence in gastroenterology.

Best practice & research. Clinical gastroenterology
Artificial intelligence is poised to revolutionize the field of medicine, however significant questions must be answered prior to its implementation on a regular basis. Many artificial intelligence algorithms remain limited by isolated datasets which...

Barrett esophagus: What to expect from Artificial Intelligence?

Best practice & research. Clinical gastroenterology
The evaluation and assessment of Barrett's esophagus is challenging for both expert and nonexpert endoscopists. However, the early diagnosis of cancer in Barrett's esophagus is crucial for its prognosis, and could save costs. Pre-clinical and clinica...

VR-Caps: A Virtual Environment for Capsule Endoscopy.

Medical image analysis
Current capsule endoscopes and next-generation robotic capsules for diagnosis and treatment of gastrointestinal diseases are complex cyber-physical platforms that must orchestrate complex software and hardware functions. The desired tasks for these s...