Colon Cancer

Neural network analysis of Chinese herbal medicine prescriptions for patients with colorectal cancer.

Traditional Chinese Medicine (TCM) is an experiential form of medicine with a history dating back thousands of years. The present study aimed to utilize neural network analysis to examine specific prescriptions for colorectal cancer (CRC) in clinical practice to arrive at the most effective prescription strategy. The study analyzed the data of 261 CRC cases recruited from a total of 141,962 cases ...

Computer-aided diagnosis using deep learning in the evaluation of early oesophageal adenocarcinoma.

Prediction of findings at screening colonoscopy using a machine learning algorithm based on complete blood counts (ColonFlag).

Adenomatous polyps are a common precursor lesion for colorectal cancer. ColonFlag is a machine- learning-based algorithm that uses basic patient infor...

A reliable method for colorectal cancer prediction based on feature selection and support vector machine.

Colorectal cancer (CRC) is a common cancer responsible for approximately 600,000 deaths per year worldwide. Thus, it is very important to find the rel...

Dual Convolutional Neural Network Based Method for Predicting Disease-Related miRNAs.

Identification of disease-related microRNAs (disease miRNAs) is helpful for understanding and exploring the etiology and pathogenesis of diseases. Mos...

LogLoss-BERAF: An ensemble-based machine learning model for constructing highly accurate diagnostic sets of methylation sites accounting for heterogeneity in prostate cancer.

Although modern methods of whole genome DNA methylation analysis have a wide range of applications, they are not suitable for clinical diagnostics due...

Comparative effectiveness of human scope assistant versus robotic scope holder in laparoscopic resection for colorectal cancer.

BACKGROUND: Several types of robotic scope holders have been developed to date, but there are only some experimental reports or the results of small c...

Human-machine collaboration: bringing artificial intelligence into colonoscopy.

Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy.

The detection and removal of precancerous polyps via colonoscopy is the gold standard for the prevention of colon cancer. However, the detection rate ...

3-D Quantification of Filopodia in Motile Cancer Cells.

We present a 3D bioimage analysis workflow to quantitatively analyze single, actin-stained cells with filopodial protrusions of diverse structural and...

An Increased Level of Aryl Hydrocarbon Receptor in Patients with Pancreatic Cancer.

BACKGROUND Aryl-carbon receptor (AhR), a ligand-activated transcription factor, is best known for its ability to mediate the effects of environmental ...

3D Deep Learning from CT Scans Predicts Tumor Invasiveness of Subcentimeter Pulmonary Adenocarcinomas.

: Identification of early-stage pulmonary adenocarcinomas before surgery, especially in cases of subcentimeter cancers, would be clinically important ...

A principled machine learning framework improves accuracy of stage II colorectal cancer prognosis.

Accurate prognosis is fundamental in planning an appropriate therapy for cancer patients. Consequent to the heterogeneity of the disease, intra- and i...

Optical classification of neoplastic colorectal polyps - a computer-assisted approach (the COACH study).

BACKGROUND AND AIMS: Clinical data suggest that the quality of optical diagnoses of colorectal polyps differs markedly among endoscopists. The aim of ...

Identify and monitor clinical variation using machine intelligence: a pilot in colorectal surgery.

Standardized clinical pathways are useful tool to reduce variation in clinical management and may improve quality of care. However the evidence suppor...

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...

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...

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...

CEA: Combination-based gene set functional enrichment analysis.

Functional enrichment analysis is a fundamental and challenging task in bioinformatics. Most of the current enrichment analysis approaches individuall...

Classification of lung adenocarcinoma transcriptome subtypes from pathological images using deep convolutional networks.

PURPOSE: Convolutional neural networks have become rapidly popular for image recognition and image analysis because of its powerful potential. In this...