GERD

May the force be with you: will artificial intelligence take over traditional endoscopy?

Charting a path forward for clinical research in artificial intelligence and gastroenterology.

Gastroenterology has been an early leader in bridging the gap between artificial intelligence (AI) model development and clinical trial validation, and in recent years we have seen the publication of several randomized clinical trials examining the role of AI in gastroenterology. As AI applications for clinical medicine advance rapidly, there is a clear need for guidance surrounding AI-specific st...

Artificial intelligence-assisted analysis of endoscopic retrograde cholangiopancreatography image for identifying ampulla and difficulty of selective cannulation.

The advancement of artificial intelligence (AI) has facilitated its application in medical fields. However, there has been little research for AI-assi...

Triage-driven diagnosis of Barrett's esophagus for early detection of esophageal adenocarcinoma using deep learning.

Deep learning methods have been shown to achieve excellent performance on diagnostic tasks, but how to optimally combine them with expert knowledge an...

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

BACKGROUND: Recent advances in robotics and deep learning can be used in endoscopic surgeries and can provide numerous advantages by freeing one of th...

State of the Art: The Impact of Artificial Intelligence in Endoscopy 2020.

PURPOSE OF REVIEW: Recently numerous researchers have shown remarkable progress using convolutional neural network-based artificial intelligence (AI) ...

Performance improvement for a 2D convolutional neural network by using SSC encoding on protein-protein interaction tasks.

BACKGROUND: The interactions of proteins are determined by their sequences and affect the regulation of the cell cycle, signal transduction and metabo...

Protein Complexes Detection Based on Semi-Supervised Network Embedding Model.

A protein complex is a group of associated polypeptide chains which plays essential roles in the biological process. Given a graph representing protei...

Identification of novel inhibitors of Keap1/Nrf2 by a promising method combining protein-protein interaction-oriented library and machine learning.

Protein-protein interactions (PPIs) are prospective but challenging targets for drug discovery, because screening using traditional small-molecule lib...

IL-8, MSPa, MIF, FGF-9, ANG-2 and AgRP collection were identified for the diagnosis of colorectal cancer based on the support vector machine model.

Colorectal cancer (CRC) is one of the most common cancer, and the early detection of CRC is essential to improve the survival rate of patients. To ide...

Sustained results of robotic mitral repair in a lower volume center with extensive minimally invasive mitral repair experience.

The literature for robotic mitral repair is dominated by a small number of large volume institutions, and intermediate-term outcomes out to 5 years ar...

Small Bowel Capsule Endoscopy and artificial intelligence: First or second reader?

Several machine learning algorithms have been developed in the past years with the aim to improve SBCE (Small Bowel Capsule Endoscopy) feasibility ens...

Deep Transfer Learning for Automated Intestinal Bleeding Detection in Capsule Endoscopy Imaging.

PURPOSE: The objective of this paper was to develop a computer-aided diagnostic (CAD) tools for automated analysis of capsule endoscopic (CE) images, ...

The evolving role of EUS-guided tissue acquisition.

The introduction of endoscopic ultrasound-guided fine-needle aspiration into clinical practice was a pivotal moment for diagnostic gastrointestinal en...

Recapitulating the Binding Affinity of Nrf2 for KEAP1 in a Cyclic Heptapeptide, Guided by NMR, X-ray Crystallography, and Machine Learning.

Macrocycles, including macrocyclic peptides, have shown promise for targeting challenging protein-protein interactions (PPIs). One PPI of high interes...

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

Gastroesophageal reflux disease (GERD) is a common disease with high prevalence, and its endoscopic severity can be evaluated using the Los Angeles cl...

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

The American Society for Gastrointestinal Endoscopy (ASGE) has proposed the "resect-and-discard" and "diagnose-and-leave" strategies for diminutive co...

Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy.

The Endoscopy Computer Vision Challenge (EndoCV) is a crowd-sourcing initiative to address eminent problems in developing reliable computer aided dete...

VR-Caps: A Virtual Environment for Capsule Endoscopy.

Current capsule endoscopes and next-generation robotic capsules for diagnosis and treatment of gastrointestinal diseases are complex cyber-physical pl...

Multi-Scale Context-Guided Deep Network for Automated Lesion Segmentation With Endoscopy Images of Gastrointestinal Tract.

Accurate lesion segmentation based on endoscopy images is a fundamental task for the automated diagnosis of gastrointestinal tract (GI Tract) diseases...