Gastroenterology

Are nucleos(t)ide analogues effective against severe outcomes in COVID-19 and hepatitis B virus coinfection?

BACKGROUND AND AIM: The impact of chronic hepatitis B virus (HBV) infection and nucleos(t)ide analogue (NUC) treatment on disease severity and clinical outcomes in patients with coronavirus 2019 (COVID-19) is unknown. The objective of this study was to determine whether HBV infection and the use of NUCs impacts mortality in patients with COVID-19.

Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial).

BACKGROUND & AIMS: Artificial intelligence-based computer-aided polyp detection (CADe) systems are intended to address the issue of missed polyps during colonoscopy. The effect of CADe during screening and surveillance colonoscopy has not previously been studied in a United States (U.S.) population.

Gastrointestinal Tract Disease Classification from Wireless Endoscopy Images Using Pretrained Deep Learning Model.

Wireless capsule endoscopy is a noninvasive wireless imaging technology that becomes increasingly popular in recent years. One of the major drawbacks ...

Role of Percutaneous Transhepatic Biliary Drainage as an Adjunct to Endoscopic Retrograde Cholangiopancreatography.

BACKGROUND: There is limited literature on the role of percutaneous transhepatic biliary drainage (PTBD) as an adjunct to endoscopic retrograde cholan...

Robotic mesh-supported pectopexy for pelvic organ prolapse: expanding the options of pelvic floor repair.

Pelvic organ prolapse affects 30-50% of the female population. For definitive treatment surgery is unavoidable. Sacrocolpopexy has been the gold stand...

Technical details for a robot-assisted hand-sewn esophago-gastric anastomosis during minimally invasive Ivor Lewis esophagectomy.

BACKGROUND: Minimally invasive Ivor Lewis esophagectomy (MIILE) provides better outcomes than open techniques, particularly in terms of post-operative...

Robotic rectal resection preserves anorectal function: Systematic review and meta-analysis.

BACKGROUND: Improving survival rates in rectal cancer patients has generated a growing interest in functional outcomes after total mesorectal excision...

Toxicity evaluation and oxidative stress response of fumaronitrile, a persistent organic pollutant (POP) of industrial waste water on tilapia fish (Oreochromis mossambicus).

The study was designed to determine the impact of acute toxicity of fumaronitrile exposure through tissue damaging, oxidative stress enzymes and histo...

Kefir modulates gut microbiota and reduces DMH-associated colorectal cancer via regulation of intestinal inflammation in adulthood offsprings programmed by neonatal overfeeding.

Obesity is associated with chronic inflammation, intestinal dysbiosis, and colorectal cancer risk. The anti-cancer effects of kefir are highlighted. H...

Detection of sarcopenic obesity and prediction of long-term survival in patients with gastric cancer using preoperative computed tomography and machine learning.

BACKGROUND: Previous studies evaluating the prognostic value of computed tomography (CT)-derived body composition data have included few patients. Thu...

Colorectal Polyp Image Detection and Classification through Grayscale Images and Deep Learning.

Colonoscopy screening and colonoscopic polypectomy can decrease the incidence and mortality rate of colorectal cancer (CRC). The adenoma detection rat...

Deep learning model for diagnosing gastric mucosal lesions using endoscopic images: development, validation, and method comparison.

BACKGROUND AND AIMS: Endoscopic differential diagnoses of gastric mucosal lesions (benign gastric ulcer, early gastric cancer [EGC], and advanced gast...

Applying interpretable deep learning models to identify chronic cough patients using EHR data.

BACKGROUND AND OBJECTIVE: Chronic cough (CC) affects approximately 10% of adults. Many disease states are associated with chronic cough, such as asthm...

Artificial intelligence-assisted colonoscopy: A prospective, multicenter, randomized controlled trial of polyp detection.

BACKGROUND: Artificial intelligence (AI) assistance has been considered as a promising way to improve colonoscopic polyp detection, but there are limi...

Accurate and Feasible Deep Learning Based Semi-Automatic Segmentation in CT for Radiomics Analysis in Pancreatic Neuroendocrine Neoplasms.

Current clinical practice or radiomics studies of pancreatic neuroendocrine neoplasms (pNENs) require manual delineation of the lesions in computed to...

Method of Tumor Pathological Micronecrosis Quantification Via Deep Learning From Label Fuzzy Proportions.

The presence of necrosis is associated with tumor progression and patient outcomes in many cancers, but existing analyses rarely adopt quantitative me...

Disease type detection in lung and colon cancer images using the complement approach of inefficient sets.

Lung and colon cancers are deadly diseases that can develop simultaneously in organs and adversely affect human life in some special cases. Although t...

Efficacy of a comprehensive binary classification model using a deep convolutional neural network for wireless capsule endoscopy.

The manual reading of capsule endoscopy (CE) videos in small bowel disease diagnosis is time-intensive. Algorithms introduced to automate this process...

Quantitative analysis of metastatic breast cancer in mice using deep learning on cryo-image data.

Cryo-imaging sections and images a whole mouse and provides ~ 120-GBytes of microscopic 3D color anatomy and fluorescence images, making fully manual ...

Diagnostic performance of endoscopic ultrasound-artificial intelligence using deep learning analysis of gallbladder polypoid lesions.

BACKGROUND AND AIM: Endoscopic ultrasound (EUS) is the most accurate diagnostic modality for polypoid lesions of the gallbladder (GB), but is limited ...