Peptic Ulcer Disease

A convolutional neural network Cascade for plantar pressure images registration.

BACKGROUND: Plantar pressure image (PPI) recorded in high spatial and temporal resolution is very useful in clinical gait analysis. For functional analysis of PPI, image registration is often performed to maximally correlate source image with a template image. Previous methods estimate the registration parameters by iteratively optimizing different objective functions. These methods are often comp...

Anticoagulant Related Nephropathy Induced by Dabigatran.

We describe a case of biopsy-proven dabigatran related nephropathy in a patient without underlying IgA nephropathy. To date, dabigatran related nephropathy was only reported in patients with concurrent or undiagnosed IgA nephropathy, suggesting that it may predispose patients to dabigatran associated injury. The patient is an 81-year-old woman with multiple medical comorbidities, including nonvalv...

A Hybrid Residual Network and Long Short-Term Memory Method for Peptic Ulcer Bleeding Mortality Prediction.

The prediction of patient mortality, which can detect high-risk patients, is a significant yet challenging problem in medical informatics. Thanks to t...

Adverse Drug Reaction Predictions Using Stacking Deep Heterogeneous Information Network Embedding Approach.

Inferring potential adverse drug reactions is an important and challenging task for the drug discovery and healthcare industry. Many previous studies ...

Application of convolutional neural network in the diagnosis of the invasion depth of gastric cancer based on conventional endoscopy.

BACKGROUND AND AIMS: According to guidelines, endoscopic resection should only be performed for patients whose early gastric cancer invasion depth is ...

Robot-assisted percutaneous placement of K-wires during minimally invasive interventions of the spine.

To assess the accuracy and time requirements of image-guided percutaneous K-wire insertion in the spine using an advanced robot assistance device for...

Estimation of Neonatal Intestinal Perforation Associated with Necrotizing Enterocolitis by Machine Learning Reveals New Key Factors.

Intestinal perforation (IP) associated with necrotizing enterocolitis (NEC) is one of the leading causes of mortality in premature neonates; with majo...

Radiofrequency endometrial ablation for treating heavy menstrual bleeding in women with chronic renal failure.

OBJECTIVE: The study objective was to retrospectively evaluate the efficacy and safety of radiofrequency endometrial ablation in treating heavy menstr...

Integrating network topology, gene expression data and GO annotation information for protein complex prediction.

The prediction of protein complexes based on the protein interaction network is a fundamental task for the understanding of cellular life as well as t...

Automatic detection of erosions and ulcerations in wireless capsule endoscopy images based on a deep convolutional neural network.

BACKGROUND AND AIMS: Although erosions and ulcerations are the most common small-bowel abnormalities found on wireless capsule endoscopy (WCE), a comp...

Ensemble of machine learning algorithms using the stacked generalization approach to estimate the warfarin dose.

Warfarin dosing remains challenging due to narrow therapeutic index and highly individual variability. Incorrect warfarin dosing is associated with de...

Comparison of 2 Natural Language Processing Methods for Identification of Bleeding Among Critically Ill Patients.

IMPORTANCE: To improve patient safety, health care systems need reliable methods to detect adverse events in large patient populations. Events are oft...

Fully automated diagnostic system with artificial intelligence using endocytoscopy to identify the presence of histologic inflammation associated with ulcerative colitis (with video).

BACKGROUND AND AIMS: In the treatment of ulcerative colitis (UC), an incremental benefit of achieving histologic healing beyond that of endoscopic muc...

Deep learning with cinematic rendering: fine-tuning deep neural networks using photorealistic medical images.

Deep learning has emerged as a powerful artificial intelligence tool to interpret medical images for a growing variety of applications. However, the p...

The utility of artificial neural networks and classification and regression trees for the prediction of endometrial cancer in postmenopausal women.

OBJECTIVE: Artificial neural networks (ANNs) and classification and regression trees (CARTs) have been previously used for the prediction of cancer in...

Artificial Fish Swarm Optimization Based Method to Identify Essential Proteins.

It is well known that essential proteins play an extremely important role in controlling cellular activities in living organisms. Identifying essentia...

Remotely Controlled Mandibular Positioning During Drug-Induced Sleep Endoscopy Toward Mandibular Advancement Device Therapy: Feasibility and Protocol.

STUDY OBJECTIVES: The potential of a remotely controlled mandibular positioner (RCMP) during sleep studies in individual patients suffering from obstr...

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 pathways are largely unclear. The aim of this study was...

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 small intestinal ulcer and erosion in wireless capsule...

The Benefit of Fentanyl in Effective Sedation and Quality of Upper Endoscopy: A Double-Blinded Randomized Trial of Fentanyl Added to Midazolam Versus Midazolam Alone for Sedation.

AIMS: Our goals were to compare the effect of adding fentanyl to midazolam in a double-blinded, randomized, placebo-controlled trial and determine if ...