Gastroenterology

Deep learning-assisted differentiation of pathologically proven atypical and typical hepatocellular carcinoma (HCC) versus non-HCC on contrast-enhanced MRI of the liver.

OBJECTIVES: To train a deep learning model to differentiate between pathologically proven hepatocellular carcinoma (HCC) and non-HCC lesions including lesions with atypical imaging features on MRI.

Classification of intestinal T-cell receptor repertoires using machine learning methods can identify patients with coeliac disease regardless of dietary gluten status.

In coeliac disease (CeD), immune-mediated small intestinal damage is precipitated by gluten, leading to variable symptoms and complications, occasionally including aggressive T-cell lymphoma. Diagnosis, based primarily on histopathological examination of duodenal biopsies, is confounded by poor concordance between pathologists and minimal histological abnormality if insufficient gluten is consumed...

Deep learning trained algorithm maintains the quality of half-dose contrast-enhanced liver computed tomography images: Comparison with hybrid iterative reconstruction: Study for the application of deep learning noise reduction technology in low dose.

PURPOSE: This study compares the image and diagnostic qualities of a DEep Learning Trained Algorithm (DELTA) for half-dose contrast-enhanced liver com...

A deep-learning-based unsupervised model on esophageal manometry using variational autoencoder.

High-resolution manometry (HRM) is the primary method for diagnosing esophageal motility disorders and its interpretation and classification are based...

Magnetically actuated intelligent hydrogel-based child-parent microrobots for targeted drug delivery.

Small intestine-targeted drug delivery by oral administration has aroused the growing interest of researchers. In this work, the child-parent microrob...

Learning Spatiotemporal Features for Esophageal Abnormality Detection From Endoscopic Videos.

Esophageal cancer is categorized as a type of disease with a high mortality rate. Early detection of esophageal abnormalities (i.e. precancerous and e...

Deep Ensemble Feature Network for Gastric Section Classification.

In this paper, we propose a novel deep ensemble feature (DEF) network to classify gastric sections from endoscopic images. Different from recent deep ...

Perioperative and long-term outcomes of robot-assisted versus laparoscopy-assisted hemicolectomy for left-sided colon cancers: a retrospective study.

The objective of this study is to evaluate the perioperative and long-term outcomes of robot-assisted hemicolectomy (RAH) versus laparoscopy-assisted ...

Noninvasive Prediction of Occult Peritoneal Metastasis in Gastric Cancer Using Deep Learning.

IMPORTANCE: Occult peritoneal metastasis frequently occurs in patients with advanced gastric cancer and is poorly diagnosed with currently available t...

Worldwide diffusion of robotic approach in general surgery.

The robotic system has overcome some laparoscopic shortcomings, such as stereoscopic 3D-magnified vision, a stable camera and flexible and tremor filt...

Fully end-to-end deep-learning-based diagnosis of pancreatic tumors.

Artificial intelligence can facilitate clinical decision making by considering massive amounts of medical imaging data. Various algorithms have been i...

Pure and Hybrid Deep Learning Models can Predict Pathologic Tumor Response to Neoadjuvant Therapy in Pancreatic Adenocarcinoma: A Pilot Study.

BACKGROUND: Neoadjuvant therapy may improve survival of patients with pancreatic adenocarcinoma; however, determining response to therapy is difficult...

State of the art in esophagectomy: robotic assistance in the abdominal phase.

Over the years, robot-assisted esophagectomy gained popularity. The current literature focused mainly on robotic assistance in the thoracic phase, whe...

Small Steatotic HCC: A Radiological Variant Associated With Improved Outcome After Ablation.

Percutaneous thermal ablation is a validated treatment option for small hepatocellular carcinoma (HCC). Steatotic HCC can be reliably detected by magn...

Application of machine learning in the diagnosis of gastric cancer based on noninvasive characteristics.

BACKGROUND: The diagnosis of gastric cancer mainly relies on endoscopy, which is invasive and costly. The aim of this study is to develop a predictive...

Robotic Left Hepatectomy for Giant Hemangioma: Technical Approach in Minimally Invasive Liver Surgery.

The Potential and the Limitations of Esophageal Robotic Surgery in Children.

INTRODUCTION:  There have been numerous reports of robotic pediatric surgery in the literature, particularly regarding urological procedures for schoo...

The role of quantitative HBsAg in the natural history of e antigen-negative chronic hepatitis B: A Tunisian prospective study.

BACKGROUND/AIMS: During the natural course of Chronic Hepatitis B (CHB) infection, differentiation between inactive carrier (IC) and HBeAg negative CH...

Robotic preservation of the left colic artery with lymph node dissection for rectal cancer - a video vignette.

Transfer learning with pre-trained deep convolutional neural networks for the automatic assessment of liver steatosis in ultrasound images.

AIM: In this paper we proposed different architectures of convolutional neural network (CNN) to classify fatty liver disease in images using only pixe...