Gastroenterology

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 are due to cirrhosis, which is an advanced stage of liver fibrosis that can be accompanied by liver failure and portal hypertension. Early detection of liver fibrosis helps in improving its treatment and prevents its progression to cirrhosis. In this work, we present a novel noninvasive method to dete...

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 with solitary hepatocellular carcinoma (HCC); unfortunately, postoperative recurrence rate remains high and there is no reliable prediction tool. We explored the potential of radiomics coupled with machine-learning algorithms to improve the predictive accuracy for HCC recurrence.

Deep-UV excitation fluorescence microscopy for detection of lymph node metastasis using deep neural network.

Deep-UV (DUV) excitation fluorescence microscopy has potential to provide rapid diagnosis with simple technique comparing to conventional histopatholo...

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 conventional therapies. Oral and suppository tacr...

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 induction of cancer through epigenetic regulation...

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 intestinal tight junction proteins, and immune respon...

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 achievable test for liver disease diagnosis. Most liver di...

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 pancreatoduodenectomy. Important in this regard is the presence of a ...

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 is characterized by the presence of non-alcoholic f...

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 surgical procedure for rectal cancer. It is believed...

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 to overcome problems in conventional endoscopic su...

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 carcinoma (HCC) beyond the Barcelona Clinic Liver Can...

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 endoscopic thyroidectomy.

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. However, there are several challenges, including l...

Stomach Deformities Recognition Using Rank-Based Deep Features Selection.

Doctor utilizes various kinds of clinical technologies like MRI, endoscopy, CT scan, etc., to identify patient's deformity during the review time. Amo...

Attention-Based Deep Neural Networks for Detection of Cancerous and Precancerous Esophagus Tissue on Histopathological Slides.

IMPORTANCE: Deep learning-based methods, such as the sliding window approach for cropped-image classification and heuristic aggregation for whole-slid...

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 polyp segmentation method has been presented.

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

BACKGROUND/OBJECTIVES: Although much has been learnt regarding pregnancy after liver transplantation, data from India are scant. Hence, we evaluated t...

Association of polymorphisms in , , and with post-induction infliximab trough level in Crohn's disease patients.

BACKGROUND: Trough levels of the post-induction serum infliximab (IFX) are associated with short-term and long-term responses of Crohn's disease patie...