Peptic Ulcer Disease

Soft hybrid intrinsically motile robot for wireless small bowel enteroscopy.

BACKGROUND: Difficulties in establishing diagnosis of small bowel (SB) disorders, prevented their effective treatment. This problem was largely resolved by wireless capsule endoscopy (WCE), which has since become the first line investigation for suspected SB disorders. Several types of WCE pills are now used in clinical practice, despite their limitations and complications. WCE pills are large, ri...

The transferability of the minimal invasive surgeon's skills to open surgery.

BACKGROUND: Robot-assisted laparoscopic surgery has gained popularity, which has contributed to a decrease in the number of open procedures. Hence a growing concern regarding the ability of laparoscopically trained surgeons to perform open surgery (e.g. due to bleeding complications) has been raised. The aim of the study was to investigate the ability of conversion to open surgery following exclus...

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...

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...