GERD

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 an inherent risk of bleeding. SB capsule endoscopy (SB-CE) is the currently accepted diagnostic procedure. The aim of this study was to develop a computer-assisted diagnosis tool for the detection of GIA.

Deep Endoscopic Visual Measurements.

Robotic endoscopic systems offer a minimally invasive approach to the examination of internal body structures, and their application is rapidly extending to cover the increasing needs for accurate therapeutic interventions. In this context, it is essential for such systems to be able to perform measurements, such as measuring the distance traveled by a wireless capsule endoscope, so as to determin...

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, recurring airway obstruction and bronchospasm. The...

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 cause in the United States. The risk of colorectal can...

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. Hence, a novel computational method for PPIs pre...

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 required for training. Such datasets are difficult to...

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 predicting Drug-Target Interactions (DTI), Protein-Prote...

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 (GI) anomalies in endoscopic video frame sequence...

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 but, for the most part, is not used for confirming ...

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 the pediatric population. Conventional diagnosis me...

Endocardial linear infarct exclusion technique for non-ischaemic functional mitral regurgitation caused by cardiac sarcoidosis: a case report.

INTRODUCTION: Damage to the posterior wall of the left ventricle (LV) can cause tethering mitral regurgitation (MR). We present a patient with non-isc...

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/inhibition) of protein-protein interactions (PPIs)....

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

Protein-protein interaction (PPI) networks are viable tools to understand cell functions, disease machinery, and drug design/repositioning. Interpreti...

PCLPred: A Bioinformatics Method for Predicting Protein-Protein Interactions by Combining Relevance Vector Machine Model with Low-Rank Matrix Approximation.

Protein-protein interactions (PPI) are key to protein functions and regulations within the cell cycle, DNA replication, and cellular signaling. Theref...

A hybrid model based on neural networks for biomedical relation extraction.

Biomedical relation extraction can automatically extract high-quality biomedical relations from biomedical texts, which is a vital step for the mining...

Completing sparse and disconnected protein-protein network by deep learning.

BACKGROUND: Protein-protein interaction (PPI) prediction remains a central task in systems biology to achieve a better and holistic understanding of c...

Predicting protein complexes using a supervised learning method combined with local structural information.

The existing protein complex detection methods can be broadly divided into two categories: unsupervised and supervised learning methods. Most of the u...

Learning-based classification of informative laryngoscopic frames.

BACKGROUND AND OBJECTIVE: Early-stage diagnosis of laryngeal cancer is of primary importance to reduce patient morbidity. Narrow-band imaging (NBI) en...

Support vector machine classifier for prediction of the metastasis of colorectal cancer.

Colorectal cancer (CRC) is one of the most common cancers and a major cause of mortality. The present study aimed to identify potential biomarkers for...

Document triage for identifying protein-protein interactions affected by mutations: a neural network ensemble approach.

The precision medicine (PM) initiative promises to identify individualized treatment depending on a patients' genetic profile and their related respon...