Gastroenterology

Patterns of Metastatic Disease in Patients with Cancer Derived from Natural Language Processing of Structured CT Radiology Reports over a 10-year Period.

Background Patterns of metastasis in cancer are increasingly relevant to prognostication and treatment planning but have historically been documented by means of autopsy series. Purpose To show the feasibility of using natural language processing (NLP) to gather accurate data from radiology reports for assessing spatial and temporal patterns of metastatic spread in a large patient cohort. Material...

Automatic segmentation of rectal tumor on diffusion-weighted images by deep learning with U-Net.

PURPOSE: Manual delineation of a rectal tumor on a volumetric image is time-consuming and subjective. Deep learning has been used to segment rectal tumors automatically on T2-weighted images, but automatic segmentation on diffusion-weighted imaging is challenged by noise, artifact, and low resolution. In this study, a volumetric U-shaped neural network (U-Net) is proposed to automatically segment ...

Simultaneous Recognition of Atrophic Gastritis and Intestinal Metaplasia on White Light Endoscopic Images Based on Convolutional Neural Networks: A Multicenter Study.

INTRODUCTION: Patients with atrophic gastritis (AG) or gastric intestinal metaplasia (GIM) have elevated risk of gastric adenocarcinoma. Endoscopic sc...

Robotic versus laparoscopic right hemicolectomy: a case-matched study.

The current gold standard surgical treatment for right colonic malignancy is the laparoscopic right hemicolectomy (LRH). However, laparoscopic surgery...

xDeep-AcPEP: Deep Learning Method for Anticancer Peptide Activity Prediction Based on Convolutional Neural Network and Multitask Learning.

Cancer is one of the leading causes of death worldwide. Conventional cancer treatment relies on radiotherapy and chemotherapy, but both methods bring ...

Robot-assisted enucleation of a giant submucosal tumor in the upper esophagus.

Few reports have demonstrated robotic surgery for large tumors in the upper esophagus. We report a case of a 52-year-old woman with a giant submucosal...

Utilizing machine learning with knockoff filtering to extract significant metabolites in Crohn's disease with a publicly available untargeted metabolomics dataset.

Metabolomic data processing pipelines have been improving in recent years, allowing for greater feature extraction and identification. Lately, machine...

A nationwide comparison of short-term outcomes after transanal, open, laparoscopic, and robot-assisted total mesorectal excision.

AIM: Laparoscopic rectal cancer surgery has several limitations. Transanal total mesorectal excision (TaTME) can potentially overcome these limitation...

Prediction of Drug-Induced Liver Toxicity Using SVM and Optimal Descriptor Sets.

Drug-induced liver toxicity is one of the significant safety challenges for the patient's health and the pharmaceutical industry. It causes terminatio...

Robotic Excision of a Duodenal Gastrointestinal Stromal Tumor.

Artificial intelligence for gastric cancer: can we make further progress?

Attention-Guided Deep Neural Network With Multi-Scale Feature Fusion for Liver Vessel Segmentation.

Liver vessel segmentation is fast becoming a key instrument in the diagnosis and surgical planning of liver diseases. In clinical practice, liver vess...

The Value of Convolutional Neural Network-Based Magnetic Resonance Imaging Image Segmentation Algorithm to Guide Targeted Controlled Release of Doxorubicin Nanopreparation.

There was an investigation of the auxiliary role of convolutional neural network- (CNN-) based magnetic resonance imaging (MRI) image segmentation alg...

Robotic Dual-Console Distal Pancreatectomy: Could it be Considered a Safe Approach and Surgical Teaching even in Pancreatic Surgery? A Retrospective Observational Study Cohort.

BACKGROUND: The study aims to assess the safety and feasibility of the robotic dual-console during a robotic distal pancreatectomy METHODS: The data o...

Evaluation of Deep Learning-Based Approaches to Segment Bowel Air Pockets and Generate Pelvic Attenuation Maps from CAIPIRINHA-Accelerated Dixon MR Images.

Attenuation correction remains a challenge in pelvic PET/MRI. In addition to the segmentation/model-based approaches, deep learning methods have shown...

Reversal of thoracic sympathectomy through robot-assisted microsurgical sympathetic trunk reconstruction with sural nerve graft and additional end-to-side coaptation of the intercostal nerves: A case report.

Thoracic sympathectomy to treat palmar hyperhidrosis (PH) has widely been performed. Many patients regret the surgery due to compensatory hyperhidrosi...

Emerging Technologies for In Vitro Inhalation Toxicology.

Respiratory toxicology remains a major research area in the 21st century since current scenario of airborne viral infection transmission and pollutant...

Effect of a deep learning-based system on the miss rate of gastric neoplasms during upper gastrointestinal endoscopy: a single-centre, tandem, randomised controlled trial.

BACKGROUND: White light endoscopy is a pivotal first-line tool for the detection of gastric neoplasms. However, gastric neoplasms can be missed during...

Adoption of New Technologies: Artificial Intelligence.

Over the past decade, artificial intelligence (AI) has been broadly applied to many aspects of human life, with recent groundbreaking successes in fac...

Efficacy and safety of an open lung ventilation strategy with staircase recruitment followed by comparison on two different modes of ventilation, in moderate ARDS in cirrhosis: A pilot randomized trial.

BACKGROUND: Mechanical ventilation in cirrhosis with acute respiratory distress syndrome (ARDS) is not widely studied. We aimed to study the effect of...