Latest AI and machine learning research in gerd for healthcare professionals.
Most surgeons are skeptical as to the feasibility of autonomous actions in surgery. Interestingly, many examples of autonomous actions already exist and have been around for years. Since the beginning of this millennium, the field of artificial intelligence (AI) has grown exponentially with the development of machine learning (ML), deep learning (DL), computer vision (CV) and natural language proc...
BACKGROUND: For eosinophilic esophagitis (EoE), a substantial diagnostic delay is still a clinically relevant phenomenon. Deep learning-based algorithms have demonstrated potential in medical image analysis. Here we establish a convolutional neuronal network (CNN)-based approach that can distinguish the appearance of EoE from normal findings and candida esophagitis.
INTRODUCTION: This study aims to construct a real-time deep convolutional neural networks (DCNNs) system to diagnose early esophageal squamous cell ca...
Few reports have demonstrated robotic surgery for large tumors in the upper esophagus. We report a case of a 52-year-old woman with a giant submucosal...
In this work, we develop a deep learning-guided fiberoptic Raman diagnostic platform to assess its ability of real-time nasopharyngeal carcinoma (NPC...
BACKGROUND: White light endoscopy is a pivotal first-line tool for the detection of gastric neoplasms. However, gastric neoplasms can be missed during...
Over the past decade, artificial intelligence (AI) has been broadly applied to many aspects of human life, with recent groundbreaking successes in fac...
BACKGROUND: Appropriate tissue tension and clear visibility of the dissection area using traction are essential for effective and safe endoscopic subm...
INTRODUCTION: Gastrointestinal endoscopic quality is operator-dependent. To ensure the endoscopy quality, we constructed an endoscopic audit and feedb...
BACKGROUND: Machine-learning algorithms and big data analytics, popularly known as 'artificial intelligence' (AI), are being developed and taken up gl...
BACKGROUND: Endoscopic injection (EI) has been considered a minimally invasive option with high success rates. However, in clinical settings where EI ...
Big data is defined as being large, varied or frequently updated, and usually generated from real-world interaction. With the unprecedented availabili...
Artificial intelligence (AI) is predicted to have profound effects on the future of video capsule endoscopy (VCE) technology. The potential lies in im...
BACKGROUND AND OBJECTIVE: Functional gastrointestinal disorders (FGIDs) are reported as worldwide gastrointestinal (GI) diseases. GI motility assessme...
OBJECTIVE: Robotic endoscopes have the potential to dramatically improve endoscopy procedures, however current attempts remain limited due to mobility...
This article reviews deep learning applications in biomedical optics with a particular emphasis on image formation. The review is organized by imaging...
Purpose High-speed videoendoscopy (HSV) is an emerging, but barely used, endoscopy technique in the clinic to assess and diagnose voice disorders beca...
BACKGROUND AND AIM: Endoscopic screening for early detection of upper gastrointestinal (UGI) lesions is important. However, population-based endoscopi...
Background Clinicians vary markedly in their ability to detect murmurs during cardiac auscultation and identify the underlying pathological features. ...