Gastroenterology

Deep learning-based image analysis reveals significant differences in the number and distribution of mucosal CD3 and γδ T cells between Crohn's disease and ulcerative colitis.

Colon mucosae of ulcerative colitis (UC) and Crohn's disease (CD) display differences in the number and distribution of immune cells that are difficult to assess by eye. Deep learning-based analysis on whole slide images (WSIs) allows extraction of complex quantitative data that can be used to uncover different inflammatory patterns. We aimed to explore the distribution of CD3 and γδ T cells in co...

Cost-effectiveness analysis of revisional Roux-en-Y gastric bypass: laparoscopic vs. robot assisted.

There is controversy over the possible advantages of the robotic technology in revisional bariatric surgery. The aim of this study is to report the experience of a high-volume bariatric center on revisional Roux-en-Y gastric bypass with robot-assisted (R-rRYGB) and laparoscopic (L-rRYGB) approaches, with regards to operative outcomes and costs. Patients who underwent R-rRYGB and L-rRYGB between 20...

Stratification of Length of Stay Prediction following Surgical Cytoreduction in Advanced High-Grade Serous Ovarian Cancer Patients Using Artificial Intelligence; the Leeds L-AI-OS Score.

(1) Background: Length of stay (LOS) has been suggested as a marker of the effectiveness of short-term care. Artificial Intelligence (AI) technologies...

Survival prediction of stomach cancer using expression data and deep learning models with histopathological images.

Accurately predicting patient survival is essential for cancer treatment decision. However, the prognostic prediction model based on histopathological...

Systematic review of academic robotic surgery curricula.

The use of robotic surgery has increased exponentially in the United States. Despite this uptick in popularity, no standardized training pathway exist...

Short-term outcomes of robot-assisted versus conventional laparoscopic surgery for mid and low rectal cancer after neoadjuvant chemoradiotherapy: a propensity score-matched analysis.

The benefits of robot-assisted laparoscopic surgery (RALS) for rectal cancer remain controversial. Only a few studies have evaluated the safety and fe...

A multidomain fusion model of radiomics and deep learning to discriminate between PDAC and AIP based on F-FDG PET/CT images.

PURPOSE: To explore a multidomain fusion model of radiomics and deep learning features based on F-fluorodeoxyglucose positron emission tomography/comp...

Interactive 3D Force/Torque Parameter Acquisition and Correlation Identification during Primary Trocar Insertion in Laparoscopic Abdominal Surgery: 5 Cases.

Laparoscopic procedures have become indispensable in gastrointestinal surgery. As a minimally invasive process, it begins with primary trocar insertio...

Robust deep learning-based forward dose calculations for VMAT on the 1.5T MR-linac.

In this work we present a framework for robust deep learning-based VMAT forward dose calculations for the 1.5T MR-linac. A convolutional neural networ...

Uncertainty-aware self-supervised neural network for livermapping with relaxation constraint.

.T1ρmapping is a promising quantitative MRI technique for the non-invasive assessment of tissue properties. Learning-based approaches can mapT1ρfrom a...

Evaluation of Preprocessing Methods on Independent Medical Hyperspectral Databases to Improve Analysis.

Currently, one of the most common causes of death worldwide is cancer. The development of innovative methods to support the early and accurate detecti...

Multifunctional microrobot with real-time visualization and magnetic resonance imaging for chemoembolization therapy of liver cancer.

Microrobots that can be precisely guided to target lesions have been studied for in vivo medical applications. However, existing microrobots have chal...

Performance of an artificial intelligence-based diagnostic support tool for early gastric cancers: Retrospective study.

OBJECTIVES: Endoscopists' abilities to diagnose early gastric cancers (EGCs) vary, especially between specialists and nonspecialists. We developed an ...

Robot-assisted duodenal switch with DaVinci Xi: surgical technique and analysis of a single-institution experience of 661 cases.

Metabolic and bariatric surgery is an effective treatment for the management of obesity and related comorbidities. Although the duodenal switch has de...

A chronicle of the pancreatoduodenectomy technique development - from the surgeon's hand to the robotic arm.

BACKGROUND: Pancreatoduodenectomy (PD) remains one of the most challenging abdominal surgical procedures.

Deep learning-based quantification of NAFLD/NASH progression in human liver biopsies.

Non-alcoholic fatty liver disease (NAFLD) affects about 24% of the world's population. Progression of early stages of NAFLD can lead to the more advan...

IBD: An Interpretable Backdoor-Detection Method via Multivariate Interactions.

Recent work has shown that deep neural networks are vulnerable to backdoor attacks. In comparison with the success of backdoor-attack methods, existin...

Deep learning-based diagnostic model for predicting complications after gastrectomy.

BACKGROUND: Gastric cancer is one of the leading causes of cancer deaths, and gastrectomy with lymph node dissection is the mainstay of treatment. Des...

Artificial intelligence and automation in endoscopy and surgery.

Modern endoscopy relies on digital technology, from high-resolution imaging sensors and displays to electronics connecting configurable illumination a...

OrganoID: A versatile deep learning platform for tracking and analysis of single-organoid dynamics.

Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug screening. Dynamic changes in individual organoid ...