Gastroenterology

Physician Review of a Celiac Disease Risk Estimation and Decision-Making Expert System.

Celiac disease is a genetic disease affecting people of all ages, resulting in small intestine enteropathy. It is considered to be a clinical chameleon. Average prevalence of celiac disease is 1 out of 100 people with data indicating the risk may be as high as 22% for those with first-degree relatives with the disease. Eighty-three percent of people with celiac disease may be undiagnosed. Average...

Localization strategies for robotic endoscopic capsules: a review.

INTRODUCTION: Nowadays, mass screening campaigns for colorectal cancer diagnosis in the early and curable stage is essential yet limited due to many reasons, for example, invasiveness, fear of pain, and embarrassment for patients. Indeed, mass screening programs, allowing precancerous lesion detection, are the most cost-effective way to reduce mortality and potentially eradicate colorectal cancer ...

Machine Learning to Predict Outcomes in Patients with Acute Gastrointestinal Bleeding: A Systematic Review.

Risk stratification of patients with gastrointestinal bleeding (GIB) is recommended, but current risk assessment tools have variable performance. Mach...

Combination of cut-log cultivated fruiting body and solid-state cultured mycelia of ameliorates CCl-induced liver injury in rats.

, a medicinal mushroom indigenous to Taiwan, possesses various pharmacological functions. The most recognized ethnopharmacological relevance of is he...

Machine learning for prediction of chemoradiation therapy response in rectal cancer using pre-treatment and mid-radiation multi-parametric MRI.

PURPOSE: To predict the neoadjuvant chemoradiation therapy (CRT) response in patients with locally advanced rectal cancer (LARC) using radiomics and d...

Dynamic contrast-enhanced computed tomography diagnosis of primary liver cancers using transfer learning of pretrained convolutional neural networks: Is registration of multiphasic images necessary?

PURPOSE: To evaluate the effect of image registration on the diagnostic performance of transfer learning (TL) using pretrained convolutional neural ne...

Diagnostic ability of artificial intelligence using deep learning analysis of cyst fluid in differentiating malignant from benign pancreatic cystic lesions.

The diagnosis of pancreatic cystic lesions remains challenging. This study aimed to investigate the diagnostic ability of carcinoembryonic antigen (CE...

Development and Validation of Machine Learning Models in Prediction of Remission in Patients With Moderate to Severe Crohn Disease.

IMPORTANCE: Biological therapies have revolutionized inflammatory bowel disease management, but many patients do not respond to biological monotherapy...

Performance of a Deep Learning Model vs Human Reviewers in Grading Endoscopic Disease Severity of Patients With Ulcerative Colitis.

IMPORTANCE: Assessing endoscopic disease severity in ulcerative colitis (UC) is a key element in determining therapeutic response, but its use in clin...

Liver tissue segmentation in multiphase CT scans using cascaded convolutional neural networks.

PURPOSE: We address the automatic segmentation of healthy and cancerous liver tissues (parenchyma, active and necrotic parts of hepatocellular carcino...

Streptococcus Gallolyticus endocarditis in patient with liver cirrhosis: a case report.

Streptococcus gallolyticus (S. gallolyticus) bacteremia is commonly associated with endocarditis and diseases of gastrointestinal tract, especially wi...

Sodium hydroxide-induced esophageal stricture via an endoscopic injection needle: a novel rabbit model of corrosive injury.

Benign strictures of the esophagus are commonly encountered in clinical practice and are difficult to manage conservatively. This study aimed to esta...

Full convolutional network based multiple side-output fusion architecture for the segmentation of rectal tumors in magnetic resonance images: A multi-vendor study.

PURPOSE: Accurate segmentation of rectal tumors is a basic and crucial task for diagnosis and treatment of rectal cancer. To avoid tedious manual deli...

A Novel Method for Classifying Liver and Brain Tumors Using Convolutional Neural Networks, Discrete Wavelet Transform and Long Short-Term Memory Networks.

Rapid classification of tumors that are detected in the medical images is of great importance in the early diagnosis of the disease. In this paper, a ...

Prediction of response after chemoradiation for esophageal cancer using a combination of dosimetry and CT radiomics.

PURPOSE: To investigate the treatment response prediction feasibility and accuracy of an integrated model combining computed tomography (CT) radiomic ...

ASO Author Reflections: The Role of Robot-Assisted Ivor Lewis Esophagectomy for Esophageal Cancer.

Association of nonalcoholic fatty liver and chronic kidney disease: An analysis of 37,825 cases from health checkup center in Taiwan.

OBJECTIVE: Nonalcoholic fatty liver (NAFLD) and chronic kidney disease (CKD) share common pathogenic mechanisms and risk factors. The relationship bet...

Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI.

OBJECTIVES: To develop and validate a proof-of-concept convolutional neural network (CNN)-based deep learning system (DLS) that classifies common hepa...

Deep Q Learning Driven CT Pancreas Segmentation With Geometry-Aware U-Net.

The segmentation of pancreas is important for medical image analysis, yet it faces great challenges of class imbalance, background distractions, and n...

Development of Simplified in Vitro P-Glycoprotein Substrate Assay and in Silico Prediction Models To Evaluate Transport Potential of P-Glycoprotein.

For efficient drug discovery and screening, it is necessary to simplify P-glycoprotein (P-gp) substrate assays and to provide in silico models that pr...