AI Medical Compendium Topic

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Narrow Band Imaging

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Endoscopic diagnosis and treatment planning for colorectal polyps using a deep-learning model.

Scientific reports
We aimed to develop a computer-aided diagnostic system (CAD) for predicting colorectal polyp histology using deep-learning technology and to validate its performance. Near-focus narrow-band imaging (NBI) pictures of colorectal polyps were retrieved f...

Improved Accuracy in Optical Diagnosis of Colorectal Polyps Using Convolutional Neural Networks with Visual Explanations.

Gastroenterology
BACKGROUND & AIMS: Narrow-band imaging (NBI) can be used to determine whether colorectal polyps are adenomatous or hyperplastic. We investigated whether an artificial intelligence (AI) system can increase the accuracy of characterizations of polyps b...

A deep learning method for delineating early gastric cancer resection margin under chromoendoscopy and white light endoscopy.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUND: Accurate delineation of cancer margins is critical for endoscopic curative resection. This study aimed to train and validate real-time fully convolutional networks for delineating the resection margin of early gastric cancer (EGC) under i...

Accuracy of artificial intelligence-assisted detection of upper GI lesions: a systematic review and meta-analysis.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Artificial intelligence (AI)-assisted detection is increasingly used in upper endoscopy. We performed a meta-analysis to determine the diagnostic accuracy of AI on detection of gastric and esophageal neoplastic lesions and Helico...

Artificial intelligence system for detecting superficial laryngopharyngeal cancer with high efficiency of deep learning.

Head & neck
BACKGROUND: There are no published reports evaluating the ability of artificial intelligence (AI) in the endoscopic diagnosis of superficial laryngopharyngeal cancer (SLPC). We presented our newly developed diagnostic AI model for SLPC detection.

Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow-band imaging.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Magnifying endoscopy with narrow-band imaging (ME-NBI) has made a huge contribution to clinical practice. However, acquiring skill at ME-NBI diagnosis of early gastric cancer (EGC) requires considerable expertise and experience. R...

Real-time assessment of video images for esophageal squamous cell carcinoma invasion depth using artificial intelligence.

Journal of gastroenterology
BACKGROUND: Although optimal treatment of superficial esophageal squamous cell carcinoma (SCC) requires accurate evaluation of cancer invasion depth, the current process is rather subjective and may vary by observer. We, therefore, aimed to develop a...

A deep learning-based system for identifying differentiation status and delineating the margins of early gastric cancer in magnifying narrow-band imaging endoscopy.

Endoscopy
BACKGROUND : Accurate identification of the differentiation status and margins for early gastric cancer (EGC) is critical for determining the surgical strategy and achieving curative resection in EGC patients. The aim of this study was to develop a r...

Diagnosis of pharyngeal cancer on endoscopic video images by Mask region-based convolutional neural network.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
OBJECTIVES: We aimed to develop an artificial intelligence (AI) system for the real-time diagnosis of pharyngeal cancers.

Identifying early gastric cancer under magnifying narrow-band images with deep learning: a multicenter study.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Narrow-band imaging with magnifying endoscopy (ME-NBI) has shown advantages in the diagnosis of early gastric cancer (EGC). However, proficiency in diagnostic algorithms requires substantial expertise and experience. In this stud...