Gastroenterology

Development and validation of an endoscopic images-based deep learning model for detection with nasopharyngeal malignancies.

BACKGROUND: Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperplasia, the positive rate for malignancy identification during biopsy is low, thus leading to delayed or missed diagnosis for nasopharyngeal malignancies upon initial attempt. Here, we aimed to develop an artificial intelligence tool to detect nasopharyngeal malignancies under endoscopic examin...

Registration-Based Organ Positioning and Joint Segmentation Method for Liver and Tumor Segmentation.

The automated segmentation of liver and tumor from CT images is of great importance in medical diagnoses and clinical treatment. However, accurate and automatic segmentation of liver and tumor is generally complicated due to the complex anatomical structures and low contrast. This paper proposes a registration-based organ positioning (ROP) and joint segmentation method for liver and tumor segmenta...

PBN11-8, a Cytotoxic Polypeptide Purified from Marine , Suppresses Invasion and Migration of Human Hepatocellular Carcinoma Cells by Targeting Focal Adhesion Kinase Pathways.

The development of antitumor drugs has attracted cancer researchers and the identification of novel antitumor lead compounds is certainly of great int...

Machine learning improves classification of preclinical models of pancreatic cancer with chemical exchange saturation transfer MRI.

PURPOSE: We sought to assess whether machine learning-based classification approaches can improve the classification of pancreatic tumor models relati...

Cascaded atrous convolution and spatial pyramid pooling for more accurate tumor target segmentation for rectal cancer radiotherapy.

Convolutional neural networks (CNNs) have become the state-of-the-art method for medical segmentation. However, repeated pooling and striding operatio...

Morphometric Evaluation of the Seminiferous Tubules and the Antioxidant Protective Effects of Gallic Acid and Quercetin in the Testis and Liver of Butyl Phthalate Treated Rats.

The antioxidant protective effects of gallic acid (GAL) and quercetin (QUE) against oxidative stress induced by di-butyl phthalate (DnBP) in the liver...

Experimental infection of Friesian bulls with Theileria orientalis (Ikeda) and effects on the haematocrit, live weight, rectal temperature and activity.

Since 2012, New Zealand has suffered from an epidemic of infectious bovine anaemia associated with T. orientalis (Ikeda), an obligate intracellular pr...

Detection of Colorectal Carcinoma Based on Microbiota Analysis Using Generalized Regression Neural Networks and Nonlinear Feature Selection.

To obtain a screening tool for colorectal cancer (CRC) based on gut microbiota, we seek here to identify an optimal classifier for CRC detection as we...

Deep learning with cinematic rendering: fine-tuning deep neural networks using photorealistic medical images.

Deep learning has emerged as a powerful artificial intelligence tool to interpret medical images for a growing variety of applications. However, the p...

G2Vec: Distributed gene representations for identification of cancer prognostic genes.

Identification of cancer prognostic genes is important in that it can lead to accurate outcome prediction and better therapeutic trials for cancer pat...

Association of Helicobacter pylori Infection With Colon Cancer and Adenomatous Polyps.

BACKGROUND AND OBJECTIVE: infection is one of the most common chronic bacterial infections in the world, especially in the developing countries. This...

Development of deep neural network for individualized hepatobiliary toxicity prediction after liver SBRT.

BACKGROUND: Accurate prediction of radiation toxicity of healthy organs-at-risks (OARs) critically determines the radiation therapy (RT) success. The ...

Improving the Accuracy of Scores to Predict Gastrostomy after Intracerebral Hemorrhage with Machine Learning.

BACKGROUND: Gastrostomy placement after intracerebral hemorrhage indicates the need for continued medical care and predicts patient dependence. Our ob...

Development and Validation of a Deep Learning System for Staging Liver Fibrosis by Using Contrast Agent-enhanced CT Images in the Liver.

Purpose To develop and validate a deep learning system (DLS) for staging liver fibrosis by using CT images in the liver. Materials and Methods DLS for...

Multiparametric ultrasomics of significant liver fibrosis: A machine learning-based analysis.

OBJECTIVE: To assess significant liver fibrosis by multiparametric ultrasomics data using machine learning.

Small Intestinal Bacterial Overgrowth in Patients With Cirrhosis.

Small intestinal bacterial overgrowth (SIBO) is defined by increased density and/or abnormal composition of microbiota in the small bowel. SIBO is oft...

Identification and characterization of antioxidative peptides derived from simulated in vitro gastrointestinal digestion of walnut meal proteins.

The aim of this study was to isolate and identify antioxidant peptides from defatted walnut meal proteins hydrolysates (DWMPH) prepared by simulated g...

Nanocomplexes composed of chitosan derivatives and β-Lactoglobulin as a carrier for anthocyanins: Preparation, stability and bioavailability in vitro.

To improve sustained-release property, stability and bioavailability of anthocyanins (ACNs) in vitro, we fabricated the nanocomplexes with chitosan hy...

Automatic polyp frame screening using patch based combined feature and dictionary learning.

Polyps in the colon can potentially become malignant cancer tissues where early detection and removal lead to high survival rate. Certain types of pol...

Robust liver vessel extraction using 3D U-Net with variant dice loss function.

PURPOSE: Liver vessel extraction from CT images is essential in liver surgical planning. Liver vessel segmentation is difficult due to the complex ves...