Gastroenterology

Consolidated domain adaptive detection and localization framework for cross-device colonoscopic images.

Automatic polyp detection has been proven to be crucial in improving the diagnosis accuracy and reducing colorectal cancer mortality during the precancerous stage. However, the performance of deep neural networks may degrade severely when being deployed to polyp data in a distinct domain. This domain distinction can be caused by different scanners, hospitals, or imaging protocols. In this paper, w...

Quality gaps in public pancreas imaging datasets: Implications & challenges for AI applications.

OBJECTIVE: Quality gaps in medical imaging datasets lead to profound errors in experiments. Our objective was to characterize such quality gaps in public pancreas imaging datasets (PPIDs), to evaluate their impact on previously published studies, and to provide post-hoc labels and segmentations as a value-add for these PPIDs.

Comparison of short-term outcomes between transthoracic and robot-assisted transmediastinal radical surgery for esophageal cancer: a prospective study.

BACKGROUND: The present study aimed to assess the lower invasiveness of robot-assisted transmediastinal radical esophagectomy by prospectively compari...

Development and performance assessment of novel machine learning models to predict pneumonia after liver transplantation.

BACKGROUND: Pneumonia is the most frequently encountered postoperative pulmonary complications (PPC) after orthotopic liver transplantation (OLT), whi...

[Minimally invasive liver surgery].

Minimally invasive liver surgery is safe and can be performed with results practically equal to those in open surgery. There are different techniques ...

Lacrimal Sac Anterior Border-Maxillary Line Distance: Effect on Endoscopic Dacryocystorhinostomy (EDCR) Surgery Results and NLDO-SS Questionnaire.

This study aimed to investigate the effect of the maxillary line (ML)-lacrimal sac anterior border (LSA) distance on the results of endoscopic dacryoc...

Robotic infant surgery with 3 mm instruments: a study in piglets of less than 10 kg body weight.

No data exist concerning the appication of a new robotic system with 3 mm instruments (Senhance®, Transenterix) in infants and small children. Therefo...

Microscope-Based Automated Quantification of Liver Fibrosis in Mice Using a Deep Learning Algorithm.

In preclinical studies that involve animal models for hepatic fibrosis, accurate quantification of the fibrosis is of utmost importance. The use of di...

Artificial neural networks for multi-omics classifications of hepato-pancreato-biliary cancers: towards the clinical application of genetic data.

PURPOSE: Several multi-omics classifications have been proposed for hepato-pancreato-biliary (HPB) cancers, but these classifications have not proven ...

Nonlinear machine learning pattern recognition and bacteria-metabolite multilayer network analysis of perturbed gastric microbiome.

The stomach is inhabited by diverse microbial communities, co-existing in a dynamic balance. Long-term use of drugs such as proton pump inhibitors (PP...

Functional outcomes after robot-assisted radical cystectomy: A review of literature.

Robot-assisted radical cystectomy has steadily gained wider acceptance among urologists compared with open and laparoscopic approaches. Robot-assisted...

Predicting treatment response from longitudinal images using multi-task deep learning.

Radiographic imaging is routinely used to evaluate treatment response in solid tumors. Current imaging response metrics do not reliably predict the un...

Artificial neural networks versus LASSO regression for the prediction of long-term survival after surgery for invasive IPMN of the pancreas.

Prediction of long-term survival in patients with invasive intraductal papillary mucinous neoplasm (IPMN) of the pancreas may aid in patient assessmen...

Emergent robotic versus laparoscopic surgery for perforated gastrojejunal ulcers: a retrospective cohort study of 44 patients.

BACKGROUND: Perforated gastrojejunal ulcers are a known complication following Roux-en-Y gastric bypass (RYGB) surgery requiring emergent surgical rep...

Small Bowel Capsule Endoscopy and artificial intelligence: First or second reader?

Several machine learning algorithms have been developed in the past years with the aim to improve SBCE (Small Bowel Capsule Endoscopy) feasibility ens...

Assessing Rectal Cancer Treatment Response Using Coregistered Endorectal Photoacoustic and US Imaging Paired with Deep Learning.

Background Conventional radiologic modalities perform poorly in the radiated rectum and are often unable to differentiate residual cancer from treatme...

High-Precision Assessment of Chemoradiotherapy of Rectal Cancer with Near-Infrared Photoacoustic Microscopy and Deep Learning.

Coupling Machine Learning and Lipidomics as a Tool to Investigate Metabolic Dysfunction-Associated Fatty Liver Disease. A General Overview.

Hepatic biopsy is the gold standard for staging nonalcoholic fatty liver disease (NAFLD). Unfortunately, accessing the liver is invasive, requires a m...

Robotic-assisted radical prostatectomy following colo-rectal surgery: a user's guide.

To assess the feasibility and operative outcomes of RARP following colo-rectal surgery. A prospective database of patients undergoing RARP is maintain...

Hypervascular Nodules and Stiffer Liver are Associated with Recurrence after Microwave Ablation in Patients with Hepatocellular Carcinoma: A Double-Center Analysis.

 The aim of this study was to detect the most important risk factors for recurrence after microwave ablation (MWA) of hepatocellular carcinoma (HCC)....