Gastroenterology

Dual adversarial convolutional networks with multilevel cues for pancreatic segmentation.

Accurate organ segmentation is a relatively challenging subject in medical imaging, especially for the pancreas, whose morphological characteristics are subtle but variable. In this paper, a novel dual adversarial convolutional network with multilevel cues (DACN-MC) is proposed to segment the pancreas in computerized tomography (CT). DACN-MC first involves a duplex adversarial network using a conv...

Predicting mortality among patients with liver cirrhosis in electronic health records with machine learning.

OBJECTIVE: Liver cirrhosis is a leading cause of death and effects millions of people in the United States. Early mortality prediction among patients with cirrhosis might give healthcare providers more opportunity to effectively treat the condition. We hypothesized that laboratory test results and other related diagnoses would be associated with mortality in this population. Our another assumption...

Prediction of permeability across intestinal cell monolayers for 219 disparate chemicals using in vitro experimental coefficients in a pH gradient system and in silico analyses by trivariate linear regressions and machine learning.

For medicines, the apparent membrane permeability coefficients (P) across human colorectal carcinoma cell line (Caco-2) monolayers under a pH gradient...

Identifying novel transcript biomarkers for hepatocellular carcinoma (HCC) using RNA-Seq datasets and machine learning.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death in the world owing to limitations in its prognosis. The curren...

Ontology Engineering for Gastric Dystemperament in Persian Medicine.

OBJECTIVE: Developing an ontology can help collecting and sharing information in traditional medicine including Persian medicine in a well-defined for...

Defining the next steps for artificial intelligence in colonoscopy.

Evaluation of novel LCI CAD EYE system for real time detection of colon polyps.

BACKGROUND: Linked color imaging (LCI) has been shown to be effective in multiple randomized controlled trials for enhanced colorectal polyp detection...

Human and rat microsomal metabolites of N-tert-butoxycarbonylmethamphetamine and its urinary metabolites in rat.

PURPOSE: N-tert-Butoxycarbonylmethamphetamine (BocMA), a masked derivative of methamphetamine (MA), converts into MA under acidic condition and potent...

An ensemble learning framework for potential miRNA-disease association prediction with positive-unlabeled data.

To explore the pathogenic mechanisms of MicroRNA (miRNA) on diverse diseases, many researchers have concentrated on discovering the potential associat...

A Molecular Hepatocellular Carcinoma Prognostic Score System Precisely Predicts Overall Survival of Hepatocellular Carcinoma Patients.

BACKGROUND AND AIMS: With high rates of recurrence post-treatment, hepatocellular carcinoma (HCC) is one of the most common types of cancer worldwide ...

Diagnosis of Wilson Disease and Its Phenotypes by Using Artificial Intelligence.

WD is caused by variants disrupting copper efflux resulting in excessive copper accumulation mainly in liver and brain. The diagnosis of WD is challe...

Automatic Polyp Segmentation in Colonoscopy Images Using a Modified Deep Convolutional Encoder-Decoder Architecture.

Colorectal cancer has become the third most commonly diagnosed form of cancer, and has the second highest fatality rate of cancers worldwide. Currentl...

Outcomes of robotic partial excision of the levator ani muscle for locally advanced low rectal cancer invading the ipsilateral pelvic floor at the anorectal ring level.

PURPOSE: The purpose of this study is to evaluate partial excision of the levator ani muscle (PELM) enables preservation of anal sphincter function al...

Deep Learning for Classifying Physical Activities from Accelerometer Data.

Physical inactivity increases the risk of many adverse health conditions, including the world's major non-communicable diseases, such as coronary hear...

Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study.

BACKGROUND: Response to immunotherapy in gastric cancer is associated with microsatellite instability (or mismatch repair deficiency) and Epstein-Barr...

A Comparison of Clinical Outcomes Between Two Different Models of Surgical Robots in Roux-en-Y Gastric Bypass.

For the past 20 years, robotic surgical systems have been used for the Roux-en-Y gastric bypass (RYGB). The da Vinci Surgical System (Intuitive Surgi...

Artificial intelligence and polyp detection in colonoscopy: Use of a single neural network to achieve rapid polyp localization for clinical use.

BACKGROUND AND AIM: Artificial intelligence has been extensively studied to assist clinicians in polyp detection, but such systems usually require exp...

Convolutional neural network-based object detection model to identify gastrointestinal stromal tumors in endoscopic ultrasound images.

BACKGROUND AND AIM: We aimed to develop a convolutional neural network (CNN)-based object detection model for the discrimination of gastric subepithel...

Robot Assisted Distal Pancreatectomy with Celiac Axis Resection (DP-CAR) for Pancreatic Cancer: Surgical Planning and Technique.

Malignant pancreatic tumors involving the celiac artery can be resected with a distal pancreatectomy, splenectomy and celiac axis resection (DP-CAR), ...

Deep learning-based gene selection in comprehensive gene analysis in pancreatic cancer.

The selection of genes that are important for obtaining gene expression data is challenging. Here, we developed a deep learning-based feature selectio...