Gastroenterology

Safety of viable embryonated eggs of the whipworm as a novel food pursuant to Regulation (EU) 2015/2283.

Following a request from the European Commission, the EFSA Panel on Nutrition, Novel Foods and Food Allergens (NDA) was asked to deliver an opinion on viable embryonated eggs of the whipworm as a novel food (NF) pursuant to Regulation (EU) 2015/2283. The applicant proposes to use the NF as a food supplement in the format of a 15-mL bottle containing 250 viable embryonated eggs of . . The target p...

Performance of deep learning for differentiating pancreatic diseases on contrast-enhanced magnetic resonance imaging: A preliminary study.

PURPOSE: The purpose of this study was to evaluate the ability of deep learning to differentiate pancreatic diseases on contrast-enhanced magnetic resonance (MR) images with the aid of generative adversarial network (GAN).

A Concentric Tube Robot System for Rigid Bronchoscopy: A Feasibility Study on Central Airway Obstruction Removal.

New robotic systems have recently emerged to assist with peripheral lung access, but a robotic system for rigid bronchoscopy has yet to be developed. ...

Recurrent Saliency Transformation Network for Tiny Target Segmentation in Abdominal CT Scans.

We aim at segmenting a wide variety of organs, including tiny targets (e.g., adrenal gland), and neoplasms (e.g., pancreatic cyst), from abdominal CT ...

Oncological and anorectal functional outcomes of robot-assisted intersphincteric resection in lower rectal cancer, particularly the extent of sphincter resection and sphincter saving.

BACKGROUND: Few investigations to date assessing the effectiveness of robot-assisted intersphincteric resection (ISR) have included sufficient patient...

Residual convolutional neural network for predicting response of transarterial chemoembolization in hepatocellular carcinoma from CT imaging.

BACKGROUND: We attempted to train and validate a model of deep learning for the preoperative prediction of the response of patients with intermediate-...

Predicting ideal outcome after pediatric liver transplantation: An exploratory study using machine learning analyses to leverage Studies of Pediatric Liver Transplantation Data.

Machine learning analyses allow for the consideration of numerous variables in order to accommodate complex relationships that would not otherwise be ...

Artificial neural networks accurately predict intra-abdominal infection in moderately severe and severe acute pancreatitis.

OBJECTIVE: The aim of this study was to evaluate the efficacy of artificial neural networks (ANN) in predicting intra-abdominal infection in moderatel...

Noninvasive Evaluation of Liver Fibrosis Reverse Using Artificial Neural Network Model for Chronic Hepatitis B Patients.

The diagnostic performance of an artificial neural network model for chronic HBV-induced liver fibrosis reverse is not well established. Our research ...

Grading of hepatocellular carcinoma based on diffusion weighted images with multiple b-values using convolutional neural networks.

PURPOSE: To effectively grade hepatocellular carcinoma (HCC) based on deep features derived from diffusion weighted images (DWI) with multiple b-value...

Reducing the Hausdorff Distance in Medical Image Segmentation With Convolutional Neural Networks.

The Hausdorff Distance (HD) is widely used in evaluating medical image segmentation methods. However, the existing segmentation methods do not attempt...

Is it possible to automatically assess pretreatment digital rectal examination documentation using natural language processing? A single-centre retrospective study.

OBJECTIVES: To develop and test a method for automatic assessment of a quality metric, provider-documented pretreatment digital rectal examination (DR...

Clinically Applicable Deep Learning Algorithm Using Quantitative Proteomic Data.

Deep learning (DL), a type of machine learning approach, is a powerful tool for analyzing large sets of data that are derived from biomedical sciences...

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data.

Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). Howe...

MRI-based treatment planning for proton radiotherapy: dosimetric validation of a deep learning-based liver synthetic CT generation method.

Magnetic resonance imaging (MRI) has been widely used in combination with computed tomography (CT) radiation therapy because MRI improves the accuracy...

Using a deep learning system in endoscopy for screening of early esophageal squamous cell carcinoma (with video).

BACKGROUND AND AIMS: Few artificial intelligence-based technologies have been developed to improve the efficiency of screening for esophageal squamous...

Synthesis and Swelling Behavior of Sodium Alginate/Poly(vinyl alcohol) Hydrogels.

OBJECTIVES: Hydrogels are macromolecular networks able to absorb and release water/biological fluids in a reverse-phase manner, in response to specifi...

MAPGI: Accurate identification of anatomical landmarks and diseased tissue in gastrointestinal tract using deep learning.

Automatic detection of anatomical landmarks and diseases in medical images is a challenging task which could greatly aid medical diagnosis and reduce ...

Raman spectroscopic histology using machine learning for nonalcoholic fatty liver disease.

Histopathology requires the expertise of specialists to diagnose morphological features of cells and tissues. Raman imaging can provide additional bio...

Utilizing hybrid functional fuzzy wavelet neural networks with a teaching learning-based optimization algorithm for medical disease diagnosis.

Accurate medical disease diagnosis is considered to be an important classification problem. The main goal of the classification process is to determin...