Gastroenterology

Computer-Aided Diagonosis for Colorectal Cancer using Deep Learning with Visual Explanations.

Detection, diagnosis, and removal of colorectal neoplasms are well-accepted colorectal cancer preven...

A V-Net Based Deep Learning Model for Segmentation and Classification of Histological Images of Gastric Ablation.

Gastric motility disorders are associated with bioelectrical abnormalities in the stomach. Recently,...

Automatic segmentation of ultrasound images of gastrocnemius medialis with different echogenicity levels using convolutional neural networks.

The purpose of this study was to develop an automatic method for the segmentation of muscle cross-se...

Assisting the Non-invasive Diagnosis of Liver Fibrosis Stages using Machine Learning Methods.

Fibrosis is a significant indication of chronic liver diseases often due to hepatitis C Virus. It is...

Artificial Intelligence for Understanding Imaging, Text, and Data in Gastroenterology.

Artificial intelligence (AI) could change the practice of gastroenterology through its ability to bo...

[Integration of production-university-research based on artificial intelligence for technological innovation and transformation in gastrointestinal surgery].

Medical artificial intelligence is a deeply integrated field of production-university-research. The ...

[Application of convolutional neural network to risk evaluation of positive circumferential resection margin of rectal cancer by magnetic resonance imaging].

To explore the feasibility of using faster regional convolutional neural network (Faster R-CNN) to ...

Ontologies for Liver Diseases Representation: A Systematic Literature Review.

Ontology, as a useful knowledge engineering technique, has been widely used for reducing ambiguity a...

Concordance Study in Hepatectomy Recommendations Between Watson for Oncology and Clinical Practice for Patients with Hepatocellular Carcinoma in China.

BACKGROUND: With the improvement in diagnostic imaging, perioperative care and surgical technique, t...

The Impact of Robotics in Learning Roux-en-Y Gastric Bypass: a Retrospective Analysis of 214 Laparoscopic and Robotic Procedures : Robotic Vs. Laparoscopic RYGB.

BACKGROUND: Proximal Roux-en-Y gastric bypass is commonly used to manage obesity, performed using la...

Deep learning to distinguish pancreatic cancer tissue from non-cancerous pancreatic tissue: a retrospective study with cross-racial external validation.

BACKGROUND: The diagnostic performance of CT for pancreatic cancer is interpreter-dependent, and app...

Study on intelligent syndrome differentiation neural network model of stomachache in traditional Chinese medicine based on the real world.

Stomachache is not only disease name of Traditional Chinese medicine (TCM) but also the clinical sym...

Comparative outcomes of robot-assisted minimally invasive versus open esophagectomy in patients with esophageal squamous cell carcinoma: a propensity score-weighted analysis.

Robots are increasingly used in minimally invasive surgery. We evaluated the clinical benefits of ro...

Emerging imaging techniques for acute pancreatitis.

Acute pancreatitis (AP) is caused by acute inflammation of the pancreas and adjacent tissue and is a...

Advanced imaging techniques for chronic pancreatitis.

MRI and MRCP play an important role in the diagnosis of chronic pancreatitis (CP) by imaging pancrea...

[A fusion network model based on limited training samples for the automatic segmentation of pelvic endangered organs].

When applying deep learning to the automatic segmentation of organs at risk in medical images, we co...

Artificial intelligence in inflammatory bowel disease: current status and opportunities.

The rise and fall of the model for end-stage liver disease score and the need for an optimized machine learning approach for liver allocation.

PURPOSE OF REVIEW: The Model for End-Stage Liver Disease (MELD) has been used to rank liver transpla...

Radiomics and Deep Learning: Hepatic Applications.

Radiomics and deep learning have recently gained attention in the imaging assessment of various live...

Use of Artificial Intelligence to Reduce Radiation Exposure at Fluoroscopy-Guided Endoscopic Procedures.

OBJECTIVES: Exposure to ionizing radiation remains a hazard for patients and healthcare providers. W...

Identification of Individuals at Increased Risk for Pancreatic Cancer in a Community-Based Cohort of Patients With Suspected Chronic Pancreatitis.

OBJECTIVES: We lack reliable methods for identifying patients with chronic pancreatitis (CP) at incr...