Colon Cancer

Real-time colorectal cancer diagnosis using PR-OCT with deep learning.

Prior reports have shown optical coherence tomography (OCT) can differentiate normal colonic mucosa ...

Machine learning to predict early recurrence after oesophageal cancer surgery.

BACKGROUND: Early cancer recurrence after oesophagectomy is a common problem, with an incidence of 2...

Cancer Prevention Using Machine Learning, Nudge Theory and Social Impact Bond.

There have been prior attempts to utilize machine learning to address issues in the medical field, p...

Classification of stomach infections: A paradigm of convolutional neural network along with classical features fusion and selection.

Automated detection and classification of gastric infections (i.e., ulcer, polyp, esophagitis, and b...

Deep Learning Features Improve the Performance of a Radiomics Signature for Predicting KRAS Status in Patients with Colorectal Cancer.

RATIONALE AND OBJECTIVES: We assess the performance of a model combining a deep convolutional neural...

Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study.

BACKGROUND: Colonoscopy with computer-aided detection (CADe) has been shown in non-blinded trials to...

Machine Learning in Prediction of Second Primary Cancer and Recurrence in Colorectal Cancer.

BACKGROUND: Colorectal cancer (CRC) is the third commonly diagnosed cancer worldwide. Recurrence of ...

Use of Artificial Intelligence-Based Analytics From Live Colonoscopies to Optimize the Quality of the Colonoscopy Examination in Real Time: Proof of Concept.

Endoscopic diagnosis and treatment planning for colorectal polyps using a deep-learning model.

We aimed to develop a computer-aided diagnostic system (CAD) for predicting colorectal polyp histolo...

Multilayer feature selection method for polyp classification via computed tomographic colonography.

Polyp classification is a feature selection and clustering process. Picking the most effective featu...

Predicting breast cancer risk using personal health data and machine learning models.

Among women, breast cancer is a leading cause of death. Breast cancer risk predictions can inform sc...

Assessment of individual tumor buds using keratin immunohistochemistry: moderate interobserver agreement suggests a role for machine learning.

Tumor budding is a promising and cost-effective biomarker with strong prognostic value in colorectal...

A modular cGAN classification framework: Application to colorectal tumor detection.

Automatic identification of tissue structures in the analysis of digital tissue biopsies remains an ...

Hollow Alginate-Poly-L-Lysine-Alginate Microspheres Promoted an Epithelial-Mesenchymal Transition in Human Colon Adenocarcinoma Cells.

Today, there is an urgent need to develop a three-dimentional culture systems mimicking native con...

A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images.

OBJECTIVE: To develop a deep learning-based artificial intelligence (AI) scheme for predicting the l...

The integrative knowledge base for miRNA-mRNA expression in colorectal cancer.

"miRNA colorectal cancer" (https://mirna-coadread.omics.si/) is a freely available web application f...

Evaluation of colorectal cancer subtypes and cell lines using deep learning.

Colorectal cancer (CRC) is a common cancer with a high mortality rate and a rising incidence rate in...

An overview of deep learning algorithms and water exchange in colonoscopy in improving adenoma detection.

: Among the Gastrointestinal (GI) Endoscopy Editorial Board top 10 topics in advances in endoscopy i...

A novel artificial intelligence system for the assessment of bowel preparation (with video).

BACKGROUND AND AIMS: The quality of bowel preparation is an important factor that can affect the eff...

Stable polyp-scene classification via subsampling and residual learning from an imbalanced large dataset.

This Letter presents a stable polyp-scene classification method with low false positive (FP) detecti...

Simultaneous shape and camera-projector parameter estimation for 3D endoscopic system using CNN-based grid-oneshot scan.

For effective in situ endoscopic diagnosis and treatment, measurement of polyp sizes is important. F...