GERD

Vessel and tissue recognition during third-space endoscopy using a deep learning algorithm.

In this study, we aimed to develop an artificial intelligence clinical decision support solution to mitigate operator-dependent limitations during complex endoscopic procedures such as endoscopic submucosal dissection and peroral endoscopic myotomy, for example, bleeding and perforation. A DeepLabv3-based model was trained to delineate vessels, tissue structures and instruments on endoscopic still...

Endoscopy Training in the Age of Artificial Intelligence: Deep Learning or Artificial Competence?

A systematic review of robot-assisted anti-reflux surgery to examine reporting standards.

Robot-assisted anti-reflux surgery (RA-ARS) is increasingly being used to treat refractory gastro-oesophageal reflux disease. The IDEAL (Idea, Develop...

Robotic single port anti-reflux surgery: Initial worldwide experience of two cases with a novel surgical approach to treat gastroesophageal reflux disease.

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...

-Complex-Based Machine Learning (HCML) for the Prediction of Protein-Protein Binding Affinity Changes upon Mutation.

Protein-protein interactions (PPIs) are involved in almost all biological processes in the cell. Understanding protein-protein interactions holds the ...

A lightweight hybrid deep learning system for cardiac valvular disease classification.

Cardiovascular diseases (CVDs) are a prominent cause of death globally. The introduction of medical big data and Artificial Intelligence (AI) technolo...

Study on image data cleaning method of early esophageal cancer based on VGG_NIN neural network.

In order to clean the mislabeled images in the esophageal endoscopy image data set, we designed a new neural network VGG_NIN. Based on the new neural ...

Design and Control of a Magnetically-Actuated Capsule Robot With Biopsy Function.

OBJECTIVE: Wireless capsule endoscopy has been well used for gastrointestinal (GI) tract diagnosis. However, it can only obtain images and cannot take...

Novel deep learning-based computer-aided diagnosis system for predicting inflammatory activity in ulcerative colitis.

BACKGROUND AND AIMS: Endoscopy is increasingly performed for evaluating patients with ulcerative colitis (UC). However, its diagnostic accuracy is lar...

RAt-CapsNet: A Deep Learning Network Utilizing Attention and Regional Information for Abnormality Detection in Wireless Capsule Endoscopy.

: The emergence of wireless capsule endoscopy (WCE) has presented a viable non-invasive mean of identifying gastrointestinal diseases in the field of ...

Graph convolutional network based virus-human protein-protein interaction prediction for novel viruses.

Computational identification of human-virus protein-protein interactions (PHIs) is a worthwhile step towards understanding infection mechanisms. Analy...

Boundary Constraint Network With Cross Layer Feature Integration for Polyp Segmentation.

Clinically, proper polyp localization in endoscopy images plays a vital role in the follow-up treatment (e.g., surgical planning). Deep convolutional ...

Revealing Unforeseen Diagnostic Image Features With Deep Learning by Detecting Cardiovascular Diseases From Apical 4-Chamber Ultrasounds.

Background With the increase of highly portable, wireless, and low-cost ultrasound devices and automatic ultrasound acquisition techniques, an automat...

DCSE:Double-Channel-Siamese-Ensemble model for protein protein interaction prediction.

BACKGROUND: Protein-protein interaction (PPI) is very important for many biochemical processes. Therefore, accurate prediction of PPI can help us bett...

A deep learning framework for identifying essential proteins based on multiple biological information.

BACKGROUND: Essential Proteins are demonstrated to exert vital functions on cellular processes and are indispensable for the survival and reproduction...

Artificial intelligence for diagnosing gastric lesions under white-light endoscopy.

BACKGROUND: The ability of endoscopists to identify gastric lesions is uneven. Even experienced endoscopists may miss or misdiagnose lesions due to he...

Robotic Transgastric Reconstruction of the Double Lumen Esophagus.

Double lumen esophagus is an extremely rare condition, developing in most cases as a complication of antireflux procedures or gastroesophageal reflux ...

SDNN-PPI: self-attention with deep neural network effect on protein-protein interaction prediction.

BACKGROUND: Protein-protein interactions (PPIs) dominate intracellular molecules to perform a series of tasks such as transcriptional regulation, info...

Innovations in GI-endoscopy.

Gastrointestinal endoscopy covers both diagnosis and therapy. Due to its diagnostic accuracy and minimal invasiveness, several innovations have been m...

Identification of upper GI diseases during screening gastroscopy using a deep convolutional neural network algorithm.

BACKGROUND AND AIMS: The clinical application of GI endoscopy for the diagnosis of multiple diseases using artificial intelligence (AI) has been limit...