Peptic Ulcer Disease

Deep Learning and Minimally Invasive Endoscopy: Automatic Classification of Pleomorphic Gastric Lesions in Capsule Endoscopy.

INTRODUCTION: Capsule endoscopy (CE) is a minimally invasive examination for evaluating the gastrointestinal tract. However, its diagnostic yield for detecting gastric lesions is suboptimal. Convolutional neural networks (CNNs) are artificial intelligence models with great performance for image analysis. Nonetheless, their role in gastric evaluation by wireless CE (WCE) has not been explored.

Managing Ulcerative Colitis and Crohn's Disease: Should the Target Be Endoscopy, Histology, or Both?

In inflammatory bowel disease (IBD), mucosal healing is the primary long-term treatment goal, encompassing both endoscopic and histological outcomes. This paper aims to overview the ability of new treatment options to promote endoscopic and histological healing and to discuss the prognostic significance of endoscopic and histological outcomes. The analysis included randomized-controlled trials (pu...

Public Imaging Datasets of Gastrointestinal Endoscopy for Artificial Intelligence: a Review.

With the advances in endoscopic technologies and artificial intelligence, a large number of endoscopic imaging datasets have been made public to resea...

Comparison of effectiveness and safety of Da Vinci robot's "3 + 1" and "4 + 1" modes of treatment for colorectal cancer.

To compare the effectiveness of the Da Vinci Surgical Robot System (DSRS) "3 + 1" and "4 + 1" models for colorectal cancer (CRC). A total of 107 patie...

What we need to do to integrate artificial intelligence into GI endoscopy.

Deep learning in negative small-bowel capsule endoscopy improves small-bowel lesion detection and diagnostic yield.

OBJECTIVES: Although several studies have shown the usefulness of artificial intelligence to identify abnormalities in small-bowel capsule endoscopy (...

Knowledge, perceptions and behaviours of endoscopists towards the use of artificial intelligence-aided colonoscopy.

BACKGROUND: Recent developments in artificial intelligence (AI) systems have enabled advancements in endoscopy. Deep learning systems, using convoluti...

Predicting Individual Response to a Web-Based Positive Psychology Intervention: A Machine Learning Approach.

Positive psychology interventions (PPIs) are effective at increasing happiness and decreasing depressive symptoms. PPIs are often administered as self...

Data-driven decision-making for precision diagnosis of digestive diseases.

Modern omics technologies can generate massive amounts of biomedical data, providing unprecedented opportunities for individualized precision medicine...

Application of artificial neural network in daily prediction of bleeding in ICU patients treated with anti-thrombotic therapy.

OBJECTIVES: Anti-thrombotic therapy is the basis of thrombosis prevention and treatment. Bleeding is the main adverse event of anti-thrombosis. Existi...

E(3) equivariant graph neural networks for robust and accurate protein-protein interaction site prediction.

Artificial intelligence-powered protein structure prediction methods have led to a paradigm-shift in computational structural biology, yet contemporar...

Improved prediction of protein-protein interactions by a modified strategy using three conventional docking software in combination.

Proteins play a crucial role in many biological processes, where their interaction with other proteins are integral. Abnormal protein-protein interact...

Bleeding at the root of the inferior mesenteric artery during robotic D3 lymph node dissection for rectal cancer - a video vignette.

Development of a deep learning model for safe direct optical trocar insertion in minimally invasive surgery: an innovative method to prevent trocar injuries.

BACKGROUND: Direct optical trocar insertion is a common procedure in laparoscopic minimally invasive surgery. However, misinterpretations of the abdom...

Robotic approach for perihilar cholangiocarcinoma: from Bismuth 1 to vascular resection.

BACKGROUND: Implementation of minimally invasive surgical approaches for perihilar cholangiocarcinoma (pCCA) has been relatively slow compared to othe...

Identifying the active ingredients of carbonized Typhae Pollen by spectrum-effect relationship combined with MBPLS, PLS, and SVM algorithms.

Typhae Pollen (TP) and its carbonized product (carbonized Typhae Pollen, CTP), as cut-and-dried herbal drugs, have been widely used in the form of sli...

Impact of robotic and open surgery on patient wound complications in gastric cancer surgery: A meta-analysis.

This meta-analysis is intended to evaluate the effect of both robotic and open-cut operations on postoperative complications of stomach carcinoma. Fro...

Non-endoscopic Applications of Machine Learning in Gastric Cancer: A Systematic Review.

PURPOSE: Gastric cancer is an important health burden characterized by high prevalence and mortality rate. Upper gastrointestinal endoscopy coupled wi...

Effect of amoxicillin and clindamycin on the gene expression of markers involved in osteoblast physiology.

BACKGROUND/PURPOSE: Amoxicillin and clindamycin are the most effective decontaminants for intraoral bone grafts before their application in bone regen...

Artificial intelligence in digestive endoscopy: recent advances.

PURPOSE OF REVIEW: With the incessant advances in information technology and its implications in all domains of our life, artificial intelligence (AI)...