Colon Cancer

Deep learning-based gene selection in comprehensive gene analysis in pancreatic cancer.

The selection of genes that are important for obtaining gene expression data is challenging. Here, w...

Resolution-based distillation for efficient histology image classification.

Developing deep learning models to analyze histology images has been computationally challenging, as...

Computer-Aided Colon Polyp Detection on High Resolution Colonoscopy Using Transfer Learning Techniques.

Colonoscopies reduce the incidence of colorectal cancer through early recognition and resecting of t...

Patterns of Metastatic Disease in Patients with Cancer Derived from Natural Language Processing of Structured CT Radiology Reports over a 10-year Period.

Background Patterns of metastasis in cancer are increasingly relevant to prognostication and treatme...

A stacking ensemble deep learning approach to cancer type classification based on TCGA data.

Cancer tumor classification based on morphological characteristics alone has been shown to have seri...

Ergonomic port placement in robotic colorectal surgery.

AIM: The aim of the study was to determine how spacing between ports and alignment of ports (oblique...

Colorectal cancer surgery: by Cambridge Medical Robotics Versius Surgical Robot System-a single-institution study. Our experience.

With the previous experiences in performing laparoscopic for over a period of 15 years and da Vinci ...

Automated sizing of colorectal polyps using computer vision.

Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: An experiment on prostate histopathology image classification.

Convolutional neural networks (CNNs) are state-of-the-art computer vision techniques for various tas...

Artificial intelligence for polyp characterization: a challenging road ahead.

Transcriptome profiling by combined machine learning and statistical R analysis identifies TMEM236 as a potential novel diagnostic biomarker for colorectal cancer.

Colorectal cancer (CRC) is a common cause of cancer-related deaths worldwide. The CRC mRNA gene expr...

Predicting Colorectal Cancer Recurrence and Patient Survival Using Supervised Machine Learning Approach: A South African Population-Based Study.

South Africa (SA) has the highest incidence of colorectal cancer (CRC) in Sub-Saharan Africa (SSA)....

Reducing adenoma miss rate of colonoscopy assisted by artificial intelligence: a multicenter randomized controlled trial.

BACKGROUND: We have developed the computer-aided detection (CADe) system using an original deep lear...

Multiclassification of Endoscopic Colonoscopy Images Based on Deep Transfer Learning.

With the continuous improvement of human living standards, dietary habits are constantly changing, w...

Multi-institutional development and external validation of machine learning-based models to predict relapse risk of pancreatic ductal adenocarcinoma after radical resection.

BACKGROUND: Surgical resection is the only potentially curative treatment for pancreatic ductal aden...

Artificial intelligence-based endoscopic diagnosis of colorectal polyps using residual networks.

Convolutional neural networks (CNNs) are widely used for artificial intelligence (AI)-based image cl...

Label-free classification of dead and live colonic adenocarcinoma cells based on 2D light scattering and deep learning analysis.

The measurement of cell viability plays an essential role in the area of cell biology. At present, t...

Machine Learning Model for Predicting Postoperative Survival of Patients with Colorectal Cancer.

PURPOSE: Machine learning (ML) is a strong candidate for making accurate predictions, as we can use ...

Current status and limitations of artificial intelligence in colonoscopy.

BACKGROUND: Artificial intelligence (AI) using deep learning methods for polyp detection (CADe) and ...

A Preliminary Study of Deep-Learning Algorithm for Analyzing Multiplex Immunofluorescence Biomarkers in Body Fluid Cytology Specimens.

INTRODUCTION: Multiplex biomarker analysis of cytological body fluid specimens is often used to assi...

Joint Detection of Tap and CEA Based on Deep Learning Medical Image Segmentation: Risk Prediction of Thyroid Cancer.

In recent years, the incidence of thyroid nodules has shown an increasing trend year by year and has...