Peptic Ulcer Disease

Ensuring patient and public involvement in the transition to AI-assisted mental health care: A systematic scoping review and agenda for design justice.

BACKGROUND: Machine-learning algorithms and big data analytics, popularly known as 'artificial intelligence' (AI), are being developed and taken up globally. Patient and public involvement (PPI) in the transition to AI-assisted health care is essential for design justice based on diverse patient needs.

Power of big data to improve patient care in gastroenterology.

Big data is defined as being large, varied or frequently updated, and usually generated from real-world interaction. With the unprecedented availability of big data, comes an obligation to maximise its potential for healthcare improvements in treatment effectiveness, disease prevention and healthcare delivery. We review the opportunities and challenges that big data brings to gastroenterology. We ...

Kvasir-Capsule, a video capsule endoscopy dataset.

Artificial intelligence (AI) is predicted to have profound effects on the future of video capsule endoscopy (VCE) technology. The potential lies in im...

Deep learning for registration of region of interest in consecutive wireless capsule endoscopy frames.

BACKGROUND AND OBJECTIVE: Functional gastrointestinal disorders (FGIDs) are reported as worldwide gastrointestinal (GI) diseases. GI motility assessme...

Enabling Autonomous Colonoscopy Intervention Using a Robotic Endoscope Platform.

OBJECTIVE: Robotic endoscopes have the potential to dramatically improve endoscopy procedures, however current attempts remain limited due to mobility...

Deep Learning in Biomedical Optics.

This article reviews deep learning applications in biomedical optics with a particular emphasis on image formation. The review is organized by imaging...

Robot-assisted laparoscopic hysterectomy for endometrial cancer in a patient with Herlyn-Werner-Wunderlich syndrome.

Herlyn-Werner-Wunderlich syndrome, a rare Mullerian duct anomaly, includes a triad of uterine didelphys, obstructed haemivagina and ipsilateral renal ...

A Deep Learning Enhanced Novel Software Tool for Laryngeal Dynamics Analysis.

Purpose High-speed videoendoscopy (HSV) is an emerging, but barely used, endoscopy technique in the clinic to assess and diagnose voice disorders beca...

Using machine-learning algorithms to identify patients at high risk of upper gastrointestinal lesions for endoscopy.

BACKGROUND AND AIM: Endoscopic screening for early detection of upper gastrointestinal (UGI) lesions is important. However, population-based endoscopi...

Recent progress of robotic head and neck surgery using a flexible single port robotic system.

We performed robotic neck surgery through a transoral or retroauricular approach (RA) using the DaVinci SP and analyzed our experiences to evaluate th...

Comparative Effectiveness of Machine Learning Approaches for Predicting Gastrointestinal Bleeds in Patients Receiving Antithrombotic Treatment.

IMPORTANCE: Anticipating the risk of gastrointestinal bleeding (GIB) when initiating antithrombotic treatment (oral antiplatelets or anticoagulants) i...

An artificial intelligence deep learning model for identification of small bowel obstruction on plain abdominal radiographs.

OBJECTIVES: Small bowel obstruction is a common surgical emergency which can lead to bowel necrosis, perforation and death. Plain abdominal X-rays are...

Neural network predicts need for red blood cell transfusion for patients with acute gastrointestinal bleeding admitted to the intensive care unit.

Acute gastrointestinal bleeding is the most common gastrointestinal cause for hospitalization. For high-risk patients requiring intensive care unit st...

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, an...

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...