Gastroenterology

Robot-assisted transthoracic hybrid esophagectomy versus open and laparoscopic hybrid esophagectomy: propensity score matched analysis of short-term outcome.

PURPOSE: Minimally invasive en-bloc esophagectomy is associated with a reduction of postoperative morbidity. This was demonstrated for both total minimally invasive and hybrid esophagectomy. However, little is known about any benefits of robotic assistance compared to the conventional minimally invasive technique, especially in hybrid procedures.

Artificial intelligence based liver portal tract region identification and quantification with transplant biopsy whole-slide images.

Liver fibrosis staging is clinically important for liver disease progression prediction. As the portal tract fibrotic quantity and size in a liver biopsy correlate with the fibrosis stage, an accurate analysis of portal tract regions is clinically critical. Manual annotations of portal tract regions, however, are time-consuming and subject to large inter- and intra-observer variability. To address...

Robotic single port anti-reflux surgery: Initial worldwide experience of two cases with a novel surgical approach to treat gastroesophageal reflux disease.

INTRODUCTION: To date, no anti-reflux operations have been reported with the new da Vinci Single-Port (single port (SP)) robotic platform. We aimed to...

Acute colonic flexures: the basis for developing an artificial intelligence-based tool for predicting the course of colonoscopy.

Tortuosity of the colon is an important parameter for predicting the course of colonoscopy. Computed tomography scans of the abdominal cavity were per...

In Silico Prediction of Human and Rat Liver Microsomal Stability via Machine Learning Methods.

Liver microsomal stability is an important property considered for the screening of drug candidates in the early stage of drug development. Determinat...

Experimental evidence of effective human-AI collaboration in medical decision-making.

Artificial Intelligence (AI) systems are precious support for decision-making, with many applications also in the medical domain. The interaction betw...

Figures do matter: A literature review of 4587 robotic pancreatic resections and their implications on training.

BACKGROUND: The use of robotic assistance in minimally invasive pancreatic resection is quickly growing.

Deep Learning-Based Automatic Detection and Grading of Motion-Related Artifacts on Gadoxetic Acid-Enhanced Liver MRI.

OBJECTIVES: The aim of this study was to develop and validate a deep learning-based algorithm (DLA) for automatic detection and grading of motion-rela...

Learning From Synthetic CT Images via Test-Time Training for Liver Tumor Segmentation.

Automatic liver tumor segmentation could offer assistance to radiologists in liver tumor diagnosis, and its performance has been significantly improve...

Cooperation between artificial intelligence and endoscopists for diagnosing invasion depth of early gastric cancer.

BACKGROUND AND STUDY AIMS: The diagnostic ability of endoscopists to determine invasion depth of early gastric cancer is not favorable. We designed an...

Preoperative data-based deep learning model for predicting postoperative survival in pancreatic cancer patients.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis even after curative resection. A deep learning-based stratification of postop...

Deep learning-based approach to the characterization and quantification of histopathology in mouse models of colitis.

Inflammatory bowel disease (IBD) is a chronic immune-mediated disease of the gastrointestinal tract. While therapies exist, response can be limited wi...

Predictive modelling for high-risk stage II colon cancer using auto-artificial intelligence.

BACKGROUND: Recently, stratification of high-risk stage II colon cancer (CC) and the need for adjuvant chemotherapy have been the focus of attention. ...

Deep learning captures selective features for discrimination of microsatellite instability from pathologic tissue slides of gastric cancer.

Microsatellite instability (MSI) status is an important prognostic marker for various cancers. Furthermore, because immune checkpoint inhibitors are m...

UC-NfNet: Deep learning-enabled assessment of ulcerative colitis from colonoscopy images.

Ulcerative colitis (UC) belongs to the inflammatory bowel disease (IBD) family, which is mainly caused by inflammation of the tissue in the colon and ...

Automated surgical workflow identification by artificial intelligence in laparoscopic hepatectomy: Experimental research.

BACKGROUND: To perform accurate laparoscopic hepatectomy (LH) without injury, novel intraoperative systems of computer-assisted surgery (CAS) for LH a...

A deep learning model with incorporation of microvascular invasion area as a factor in predicting prognosis of hepatocellular carcinoma after R0 hepatectomy.

INTRODUCTION: Microvascular invasion (MVI) is a known risk factor for prognosis after R0 liver resection for hepatocellular carcinoma (HCC). The aim o...

Exposure to nitrate induces alterations in blood parameter responses, liver immunity, and lipid metabolism in juvenile turbot (Scophthalmus maximus).

Nitrate (NO) pollution of waterbodies has attracted significant global attention as it poses a serious threat to aquatic organisms and human beings. T...

Automated Detection and Characterization of Colon Cancer with Deep Convolutional Neural Networks.

Colon cancer is a momentous reason for illness and death in people. The conclusive diagnosis of colon cancer is made through histological examination....

Impact of Hospital Volume on Utilization of Minimally Invasive Surgery for Gastric Cancer.

BACKGROUND: Minimally invasive surgery (MIS) for gastric cancer is increasingly performed. The purpose of this study is to evaluate trends in utilizat...