Gastroenterology

Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps.

Colorectal polyps are known to be potential precursors to colorectal cancer, which is one of the lea...

Application of artificial intelligence in gastrointestinal endoscopy.

With recent significant improvements in artificial intelligence (AI), especially in the field of dee...

Emblicanin rich extract encapsulated double emulsion: controlled release of bioactive during phagocytosis and in vitro digestion.

ABSTRACT: Controlled release of Emblicanin rich water soluble extract of (EEO) from the inner phase...

Deep learning algorithms for automated detection of Crohn's disease ulcers by video capsule endoscopy.

BACKGROUND AND AIMS: The aim of our study was to develop and evaluate a deep learning algorithm for ...

Detecting liver fibrosis using a machine learning-based approach to the quantification of the heart-induced deformation in tagged MR images.

Liver disease causes millions of deaths per year worldwide, and approximately half of these cases ar...

Machine-learning analysis of contrast-enhanced CT radiomics predicts recurrence of hepatocellular carcinoma after resection: A multi-institutional study.

BACKGROUND: Current guidelines recommend surgical resection as the first-line option for patients wi...

Simple water-based tacrolimus enemas for refractory proctitis.

BACKGROUND AND AIMS: Rectal ulcerative colitis (UC) and Crohn's disease (CD) often do not respond to...

A gastric cancer LncRNAs model for MSI and survival prediction based on support vector machine.

BACKGROUND: Recent studies have shown that long non-coding RNAs (lncRNAs) play a crucial role in the...

Effects of multi-strain probiotic supplementation on intestinal microbiota, tight junctions, and inflammation in young broiler chickens challenged with Salmonella enterica subsp. enterica.

OBJECTIVE: This study assessed the effects of probiotics on cecal microbiota, gene expression of int...

Liver disease screening based on densely connected deep neural networks.

Liver disease is an important public health problem. Liver Function Tests (LFT) is the most achievab...

The potential of machine learning to predict postoperative pancreatic fistula based on preoperative, non-contrast-enhanced CT: A proof-of-principle study.

BACKGROUND: Postoperative pancreatic fistula remains an unsolved challenge after pancreatoduodenecto...

Non-invasive diagnosis of non-alcoholic steatohepatitis and fibrosis with the use of omics and supervised learning: A proof of concept study.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) affects 25-30% of the general population and i...

Predictive models with the use of omics and supervised machine learning to diagnose non-alcoholic fatty liver disease: A "non-invasive alternative" to liver biopsy?

Transanal total mesorectal excision for rectal cancer: a multicentric cohort study.

BACKGROUND: Transanal total mesorectal excision (taTME) has recently emerged as a promising novel su...

Surgical experience of using the endoscope manipulator robot EMARO in totally extraperitoneal inguinal hernia repair: A case report.

Robot-assisted surgery has advanced rapidly since the 1980s. However, new equipment is still needed ...

Utilizing Machine Learning for Pre- and Postoperative Assessment of Patients Undergoing Resection for BCLC-0, A and B Hepatocellular Carcinoma: Implications for Resection Beyond the BCLC Guidelines.

BACKGROUND: There is an ongoing debate about expanding the resection criteria for hepatocellular car...

Safety and efficacy of transoral robotic and endoscopic thyroidectomy: The first 100 cases.

BACKGROUND: The aim of this study was to evaluate the safety and efficacy of transoral robotic and e...

Incorporating prior shape knowledge via data-driven loss model to improve 3D liver segmentation in deep CNNs.

PURPOSE: Convolutional neural networks (CNNs) have obtained enormous success in liver segmentation. ...

Stomach Deformities Recognition Using Rank-Based Deep Features Selection.

Doctor utilizes various kinds of clinical technologies like MRI, endoscopy, CT scan, etc., to identi...

Automated polyp segmentation for colonoscopy images: A method based on convolutional neural networks and ensemble learning.

PURPOSE: To automatically and efficiently segment the lesion area of the colonoscopy polyp image, a ...

Pregnancy After Liver Transplantation: Outcomes From a Single-Center Experience.

BACKGROUND/OBJECTIVES: Although much has been learnt regarding pregnancy after liver transplantation...