Gastroenterology

A Liver Segmentation Method Based on the Fusion of VNet and WGAN.

Accurate segmentation of liver images is an essential step in liver disease diagnosis, treatment planning, and prognosis. In recent years, although liver segmentation methods based on 2D convolutional neural networks have achieved good results, there is still a lack of interlayer information that causes severe loss of segmentation accuracy to a certain extent. Meanwhile, making the best of high-le...

MISSIM: An Incremental Learning-Based Model With Applications to the Prediction of miRNA-Disease Association.

In the past few years, the prediction models have shown remarkable performance in most biological correlation prediction tasks. These tasks traditionally use a fixed dataset, and the model, once trained, is deployed as is. These models often encounter training issues such as sensitivity to hyperparameter tuning and "catastrophic forgetting" when adding new data. However, with the development of bi...

DMFMDA: Prediction of Microbe-Disease Associations Based on Deep Matrix Factorization Using Bayesian Personalized Ranking.

Identifying the microbe-disease associations is conducive to understanding the pathogenesis of disease from the perspective of microbe. In this paper,...

A Deep Learning Approach for Colonoscopy Pathology WSI Analysis: Accurate Segmentation and Classification.

Colorectal cancer (CRC) is one of the most life-threatening malignancies. Colonoscopy pathology examination can identify cells of early-stage colon tu...

Multi-Source Transfer Learning Via Multi-Kernel Support Vector Machine Plus for B-Mode Ultrasound-Based Computer-Aided Diagnosis of Liver Cancers.

B-mode ultrasound (BUS) imaging is a routine tool for diagnosis of liver cancers, while contrast-enhanced ultrasound (CEUS) provides additional inform...

Mutual-Prototype Adaptation for Cross-Domain Polyp Segmentation.

Accurate segmentation of the polyps from colonoscopy images provides useful information for the diagnosis and treatment of colorectal cancer. Despite ...

Laparoscopic Versus Robot-Assisted Versus Transanal Low Anterior Resection: 3-Year Oncologic Results for a Population-Based Cohort in Experienced Centers.

BACKGROUND: Laparoscopic, robot-assisted, and transanal total mesorectal excision are the minimally invasive techniques used most for rectal cancer su...

Artificial intelligence for detecting superficial esophageal squamous cell carcinoma under multiple endoscopic imaging modalities: A multicenter study.

BACKGROUND AND AIM: Diagnosis of esophageal squamous cell carcinoma (ESCC) is complicated and requires substantial expertise and experience. This stud...

Repeatability and reproducibility of deep-learning-based liver volume and Couinaud segment volume measurement tool.

PURPOSE: Volumetric and health assessment of the liver is crucial to avoid poor post-operative outcomes following liver resection surgery. No current ...

An artificial intelligence model to predict hepatocellular carcinoma risk in Korean and Caucasian patients with chronic hepatitis B.

BACKGROUND & AIMS: Several models have recently been developed to predict risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B ...

Feasibility of using the postauricular-groove approach without endoscopic assistant for excision of parotid tumors. Results from a series of 58 cases.

The aim of the study was to evaluate the efficacy and preliminary outcomes of using a postauricular-groove approach without endoscopic assistance for ...

Pancreatic Cancer Survival Prediction: A Survey of the State-of-the-Art.

Cancer early detection increases the chances of survival. Some cancer types, like pancreatic cancer, are challenging to diagnose or detect early, and ...

Deep learning-based endoscopic anatomy classification: an accelerated approach for data preparation and model validation.

BACKGROUND: Photodocumentation during endoscopy procedures is one of the indicators for endoscopy performance quality; however, this indicator is diff...

Robotic intersphincteric resection with bilateral seminal vesicle excision in a case of locally advanced rectal cancer - A video vignette.

Transhiatal robot-assisted minimally invasive esophagectomy: unclear benefits compared to traditional transhiatal esophagectomy.

Esophagectomy is a high-risk operation, regardless of technique. Minimally invasive transthoracic esophagectomy could reduce length of stay and pulmon...

An automated liver segmentation in liver iron concentration map using fuzzy c-means clustering combined with anatomical landmark data.

BACKGROUND: To estimate median liver iron concentration (LIC) calculated from magnetic resonance imaging, excluded vessels of the liver parenchyma reg...

Deep learning-based virtual cytokeratin staining of gastric carcinomas to measure tumor-stroma ratio.

The tumor-stroma ratio (TSR) determined by pathologists is subject to intra- and inter-observer variability. We aimed to develop a computational quant...

Artificial Intelligence and Capsule Endoscopy: Automatic Detection of Small Bowel Blood Content Using a Convolutional Neural Network.

INTRODUCTION: Capsule endoscopy has revolutionized the management of patients with obscure gastrointestinal bleeding. Nevertheless, reading capsule en...

Heller myotomy perforation: robotic visualization decreases perforation rate and revisional surgery is a perforation risk.

Minimally invasive surgery (MIS) has improved surgical access to the foregut. While the benefits of MIS versus open surgery are well accepted, the rel...

Web-based and machine learning approaches for identification of patient-reported outcomes in inflammatory bowel disease.

BACKGROUND: Messages from an Internet forum are raw material that emerges in a natural setting (i.e., non-induced by a research situation).