Peptic Ulcer Disease

Systematic review with meta-analysis: artificial intelligence in the diagnosis of oesophageal diseases.

BACKGROUND: Artificial intelligence (AI) has recently been applied to endoscopy and questionnaires for the evaluation of oesophageal diseases (ODs).

Spatio-temporal deep learning for automatic detection of intracranial vessel perforation in digital subtraction angiography during endovascular thrombectomy.

Intracranial vessel perforation is a peri-procedural complication during endovascular therapy (EVT). Prompt recognition is important as its occurrence is strongly associated with unfavorable treatment outcomes. However, perforations can be hard to detect because they are rare, can be subtle, and the interventionalist is working under time pressure and focused on treatment of vessel occlusions. Aut...

Anemia or other comorbidities? using machine learning to reveal deeper insights into the drivers of acute coronary syndromes in hospital admitted patients.

Acute coronary syndromes (ACS) are a leading cause of deaths worldwide, yet the diagnosis and treatment of this group of diseases represent a signific...

Automated detection of ulcers and erosions in capsule endoscopy images using a convolutional neural network.

Capsule endoscopy (CE) is an important tool in the management of patients with known or suspected inflammatory bowel disease. Ulcers and erosions of t...

Digital Subtraction Angiography Image Features under the Deep Learning Algorithm in Cardiovascular Interventional Treatment and Nursing for Vascular Restenosis.

The objective of this study was to explore the application value of digital subtraction angiography (DSA) images optimized by deep learning algorithms...

Comparison of Higher-Than-Standard to D-Dimer Driven Thromboprophylaxis in Hospitalized Patients With COVID-19.

Coronavirus disease 2019 is a global health threat often accompanied with coagulopathy. Despite use of thromboprophylaxis in this population, thrombo...

Deep Learning and Device-Assisted Enteroscopy: Automatic Detection of Gastrointestinal Angioectasia.

: Device-assisted enteroscopy (DAE) allows deep exploration of the small bowel and combines diagnostic and therapeutic capacities. Suspected mid-gastr...

Deep Learning-Based Cervical Spine Posterior Percutaneous Endoscopic Disc Nucleus Resection for the Treatment of Cervical Spondylotic Radiculopathy.

In the past 10 years, the technology of percutaneous spine endoscopy has been continuously developed. The indications have expanded from simple lumbar...

Real-time automated diagnosis of colorectal cancer invasion depth using a deep learning model with multimodal data (with video).

BACKGROUND AND AIMS: The optical diagnosis of colorectal cancer (CRC) invasion depth with white light (WL) and image-enhanced endoscopy (IEE) remains ...

Integrated Multiomics Analysis Identifies a Novel Biomarker Associated with Prognosis in Intracerebral Hemorrhage.

Existing treatments for intracerebral hemorrhage (ICH) are unable to satisfactorily prevent development of secondary brain injury after ICH and multip...

Artificial Intelligence and Deep Learning for Upper Gastrointestinal Neoplasia.

Upper gastrointestinal (GI) neoplasia account for 35% of GI cancers and 1.5 million cancer-related deaths every year. Despite its efficacy in preventi...

Predicting deleterious missense genetic variants via integrative supervised nonnegative matrix tri-factorization.

Among an assortment of genetic variations, Missense are major ones which a small subset of them may led to the upset of the protein function and ultim...

A Deep Learning Framework for Gene Ontology Annotations With Sequence- and Network-Based Information.

Knowledge of protein functions plays an important role in biology and medicine. With the rapid development of high-throughput technologies, a huge num...

A Novel Feature Selection Method for Uncertain Features: An Application to the Prediction of Pro-/Anti-Longevity Genes.

Understanding the ageing process is a very challenging problem for biologists. To help in this task, there has been a growing use of classification me...

Deep reconstruction-recoding network for unsupervised domain adaptation and multi-center generalization in colonoscopy polyp detection.

BACKGROUND AND OBJECTIVE: Currently, the best performing methods in colonoscopy polyp detection are primarily based on deep neural networks (DNNs), wh...

Robotic Transvaginal Natural Orifice Transluminal Endoscopic Surgery for Resection of Parametrial and Bowel Deeply Infiltrated Endometriosis.

STUDY OBJECTIVE: To demonstrate stepwise techniques for the successful utilization of the Robotic-assisted transvaginal Natural Orifice Transluminal E...

Upper endoscopy photodocumentation quality evaluation with novel deep learning system.

OBJECTIVES: Visualization and photodocumentation during endoscopy procedures are suggested to be one indicator for endoscopy performance quality. Howe...

Detecting colon polyps in endoscopic images using artificial intelligence constructed with automated collection of annotated images from an endoscopy reporting system.

BACKGROUND: Artificial intelligence (AI) has made considerable progress in image recognition, especially in the analysis of endoscopic images. The ava...

Utilization of Ultrasonic Image Characteristics Combined with Endoscopic Detection on the Basis of Artificial Intelligence Algorithm in Diagnosis of Early Upper Gastrointestinal Cancer.

The aim of this study was to evaluate the diagnostic value of artificial intelligence algorithm combined with ultrasound endoscopy in early esophageal...

Combination of artificial intelligence-based endoscopy and miR148a methylation for gastric indefinite dysplasia diagnosis.

BACKGROUND AND AIM: Gastrointestinal endoscopy and biopsy-based pathological findings are needed to diagnose early gastric cancer. However, the inform...