Gastroenterology

Robotic total intersphincteric resection with total mesorectal excision in low rectal cancer - a video vignette.

Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning.

The early detection and accurate histopathological diagnosis of gastric cancer increase the chances of successful treatment. The worldwide shortage of pathologists offers a unique opportunity for the use of artificial intelligence assistance systems to alleviate the workload and increase diagnostic accuracy. Here, we report a clinically applicable system developed at the Chinese PLA General Hospit...

Pancreatic Cancer Imaging: A New Look at an Old Problem.

Computed tomography is the most commonly used imaging modality to detect and stage pancreatic cancer. Previous advances in pancreatic cancer imaging h...

[Robot-controlled MRI-guided transrectal prostate biopsy, a promising technique].

At the so-called in-bore, MRI-guided prostate biopsy, the radiologist in the MRI suite manually directs a rectal biopsy needle guide at an abnormality...

Long-Term Bowel Sound Monitoring and Segmentation by Wearable Devices and Convolutional Neural Networks.

Bowel sounds (BSs), typically generated by the intestinal peristalses, are a significant physiological indicator of the digestive system's health cond...

Characterization of patients with advanced chronic pancreatitis using natural language processing of radiology reports.

STUDY AIM: To develop and apply a natural language processing algorithm for characterization of patients diagnosed with chronic pancreatitis in a dive...

Challenging detection of hard-to-find gastric cancers with artificial intelligence-assisted endoscopy.

Application of Deep Learning for Early Screening of Colorectal Precancerous Lesions under White Light Endoscopy.

METHODS: We collected and sorted out the white light endoscopic images of some patients undergoing colonoscopy. The convolutional neural network model...

Learning machine approach reveals microbial signatures of diet and sex in dog.

The characterization of the microbial population of many niches of the organism, as the gastrointestinal tract, is now possible thanks to the use of h...

Capsule robot for gut microbiota sampling using shape memory alloy spring.

BACKGROUND: Human gut microbiota can provide lifelong health information and even influence mood and behaviour. We currently lack the tools to obtain ...

Time-series cardiovascular risk factors and receipt of screening for breast, cervical, and colon cancer: The Guideline Advantage.

BACKGROUND: Cancer is the second leading cause of death in the United States. Cancer screenings can detect precancerous cells and allow for earlier di...

Deep learning based genome analysis and NGS-RNA LL identification with a novel hybrid model.

The conventional image segmentation techniques have a lot of issues with highest computational cost and low level accuracy for medical image diagnosis...

Artificial neural network model for preoperative prediction of severe liver failure after hemihepatectomy in patients with hepatocellular carcinoma.

BACKGROUND: Posthepatectomy liver failure is a worrisome complication after major hepatectomy for hepatocellular carcinoma and is the leading cause of...

Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes.

In clinical trials, animal and cell line models are often used to evaluate the potential toxic effects of a novel compound or candidate drug before pr...

Real-time assessment of video images for esophageal squamous cell carcinoma invasion depth using artificial intelligence.

BACKGROUND: Although optimal treatment of superficial esophageal squamous cell carcinoma (SCC) requires accurate evaluation of cancer invasion depth, ...

Deep learning and level set approach for liver and tumor segmentation from CT scans.

PURPOSE: Segmentation of liver organ and tumors from computed tomography (CT) scans is an important task for hepatic surgical planning. Manual segment...

ASO Author Reflections: Development and Validation of a Novel Risk Score Using Machine-Learning Methodology to Predict Recurrence After Hepatectomy for Colorectal Liver Metastases.

A machine learning approach identified a diagnostic model for pancreatic cancer through using circulating microRNA signatures.

Late diagnosis of pancreatic cancer (PC) due to the limited effectiveness of modern testing approaches, causes many patients to miss the chance of sur...

Esophagus segmentation from planning CT images using an atlas-based deep learning approach.

BACKGROUND AND OBJECTIVE: One of the main steps in the planning of radiotherapy (RT) is the segmentation of organs at risk (OARs) in Computed Tomograp...

Anatomical classification of upper gastrointestinal organs under various image capture conditions using AlexNet.

BACKGROUND: Machine learning has led to several endoscopic studies about the automated localization of digestive lesions and prediction of cancer inva...