Gastroenterology

Peptic Ulcer Disease

Latest AI and machine learning research in peptic ulcer disease for healthcare professionals.

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Showing 778-798 of 3,598 articles
Integration of Gene Expression Profile Data to Screen and Verify Hub Genes Involved in Osteoarthritis.

Osteoarthritis (OA) is one of the most common diseases worldwide, but the pathogenic genes and pathw...

Computer-aided detection of small intestinal ulcer and erosion in wireless capsule endoscopy images.

A novel computer-aided detection method based on deep learning framework was proposed to detect smal...

Establishment of a SVM classifier to predict recurrence of ovarian cancer.

Gene expression data using retrieved ovarian cancer (OC) samples were used to identify genes of inte...

Deep Neural Network Based Predictions of Protein Interactions Using Primary Sequences.

Machine learning based predictions of protein⁻protein interactions (PPIs) could provide valuable ins...

Postoperative bleeding risk prediction for patients undergoing colorectal surgery.

BACKGROUND: There is limited consensus regarding risk factors for postoperative bleeding. The object...

A neural network algorithm for detection of GI angiectasia during small-bowel capsule endoscopy.

BACKGROUND AND AIMS: GI angiectasia (GIA) is the most common small-bowel (SB) vascular lesion, with ...

Deep Endoscopic Visual Measurements.

Robotic endoscopic systems offer a minimally invasive approach to the examination of internal body s...

Presentation and diagnosis of patients with type 3 von Willebrand disease in resources-limited laboratory.

Von Willebrand disease (VWD) is a bleeding disorder that results from decreased von Willebrand facto...

Identification of differentially expressed genes associated with asthma in children based on the bioanalysis of the regulatory network.

Asthma, the most common chronic respiratory tract disease in children, is characterized by allergy, ...

Deep learning and conditional random fields-based depth estimation and topographical reconstruction from conventional endoscopy.

Colorectal cancer is the fourth leading cause of cancer deaths worldwide and the second leading caus...

Protein-Protein Interactions Prediction via Multimodal Deep Polynomial Network and Regularized Extreme Learning Machine.

Predicting the protein-protein interactions (PPIs) has played an important role in many applications...

Unsupervised Reverse Domain Adaptation for Synthetic Medical Images via Adversarial Training.

To realize the full potential of deep learning for medical imaging, large annotated datasets are req...

Neural networks for link prediction in realistic biomedical graphs: a multi-dimensional evaluation of graph embedding-based approaches.

BACKGROUND: Link prediction in biomedical graphs has several important applications including predic...

Detecting and Locating Gastrointestinal Anomalies Using Deep Learning and Iterative Cluster Unification.

This paper proposes a novel methodology for automatic detection and localization of gastrointestinal...

Automated classification of celiac disease during upper endoscopy: Status quo and quo vadis.

A large amount of digital image material is routinely captured during esophagogastroduodenoscopies b...

Gene expression profiles reveal key genes for early diagnosis and treatment of adamantinomatous craniopharyngioma.

Adamantinomatous craniopharyngioma (ACP) is an aggressive brain tumor that occurs predominantly in t...

Identification of Clinically Meaningful Plasma Transfusion Subgroups Using Unsupervised Random Forest Clustering.

Statistical techniques such as propensity score matching and instrumental variable are commonly empl...

Annotating activation/inhibition relationships to protein-protein interactions using gene ontology relations.

BACKGROUND: Signaling pathways can be reconstructed by identifying 'effect types' (i.e. activation/i...

MTGO: PPI Network Analysis Via Topological and Functional Module Identification.

Protein-protein interaction (PPI) networks are viable tools to understand cell functions, disease ma...

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