Peptic Ulcer Disease

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 largely affected by the subjectivity of endoscopists' experience and scoring methods, and scoring of selected endoscopic images cannot reflect the inflammation of the entire intestine. We aimed to develop an automatic scoring system using deep-learning ...

Artificial Intelligence and Machine Learning in Patient Blood Management: A Scoping Review.

Machine learning (ML) and artificial intelligence (AI) are widely used in many different fields of modern medicine. This narrative review gives, in the first part, a brief overview of the methods of ML and AI used in patient blood management (PBM) and, in the second part, aims at describing which fields have been analyzed using these methods so far. A total of 442 articles were identified by a lit...

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 ...

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...

A new brain tumor diagnostic model: Selection of textural feature extraction algorithms and convolution neural network features with optimization algorithms.

Brain tumors are one of the most dangerous diseases that affect human health and maybe result in death. Detection of brain tumors can be made by using...

Solubility Optimization of Loxoprofen as a Nonsteroidal Anti-Inflammatory Drug: Statistical Modeling and Optimization.

Industrial-based application of supercritical CO (SCCO) has emerged as a promising technology in numerous scientific fields due to offering brilliant ...

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...

Nitrogen and Chemical Control Management Improve Yield and Quality in High-Density Planting of Maize by Promoting Root-Bleeding Sap and Nutrient Absorption.

High-density planting aggravates competition among plants and has a negative impact on plant growth and productivity. Nitrogen application and chemica...

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...

Artificial intelligence implementation in pancreaticobiliary endoscopy.

INTRODUCTION: Artificial intelligence has been rapidly deployed in gastroenterology and endoscopy. The acceleration of deep convolutional neural netwo...

Robotics in therapeutic endoscopy (with video).

Since its inception, endoscopy has evolved from a solely diagnostic procedure to an expanding therapeutic field within gastroenterology. The incorpora...

See-Through Vision With Unsupervised Scene Occlusion Reconstruction.

Among the greatest of the challenges of minimally invasive surgery (MIS) is the inadequate visualisation of the surgical field through keyhole incisio...

EPGAT: Gene Essentiality Prediction With Graph Attention Networks.

Identifying essential genes and proteins is a critical step towards a better understanding of human biology and pathology. Computational approaches he...

The robotic-assisted extended "Sistrunk" approach for tumors of the upper aerodigestive tract with limited transoral access: First description of oncological and functional outcomes.

We report on the first clinical experience with the robotic-assisted extended "Sistrunk" approach (RESA) for access to constrained spaces of the upper...

A deep learning-based model improves diagnosis of early gastric cancer under narrow band imaging endoscopy.

BACKGROUND: Diagnosis of early gastric cancer (EGC) under narrow band imaging endoscopy (NBI) is dependent on expertise and skills. We aimed to elucid...