Colon Cancer

Strengths and Weaknesses of an Artificial Intelligence Polyp Detection Program as Assessed by a High-Detecting Endoscopist.

COVID-CCD-Net: COVID-19 and colon cancer diagnosis system with optimized CNN hyperparameters using gradient-based optimizer.

Coronavirus disease-2019 (COVID-19) is a new types of coronavirus which have turned into a pandemic ...

Bioinformatics analysis reveals immune prognostic markers for overall survival of colorectal cancer patients: a novel machine learning survival predictive system.

OBJECTIVES: Immune microenvironment was closely related to the occurrence and progression of colorec...

Robot-Assisted Right Colectomy with Sequential Wedge Resection of Segments 4 and 5 of The Liver and Cholecystectomy for Colon Cancer with Metastasis to The Liver.

The liver is the most common place for colon adenocarcinoma metastasis because of portal circulation...

Protection against ulcerative colitis and colorectal cancer by evodiamine via anti‑inflammatory effects.

Evodiamine (Evo) is an alkaloid that can be extracted from the berry fruit and has been reported to...

Deep learning based on hematoxylin-eosin staining outperforms immunohistochemistry in predicting molecular subtypes of gastric adenocarcinoma.

In gastric cancer (GC), there are four molecular subclasses that indicate whether patients respond t...

Although depth prediction of colorectal cancer with artificial intelligence is clinically relevant, standardization of histopathologic diagnosis should also be taken care of.

Colon Cancer Grading Using Infrared Spectroscopic Imaging-Based Deep Learning.

Tumor grade assessment is critical to the treatment of cancers. A pathologist typically evaluates gr...

The robotic learning curve for a newly appointed colorectal surgeon.

Robotic colorectal surgery allows for better ergonomics, superior retraction, and fine movements in ...

A retrospective analysis using deep-learning models for prediction of survival outcome and benefit of adjuvant chemotherapy in stage II/III colorectal cancer.

PURPOSE: Most of Stage II/III colorectal cancer (CRC) patients can be cured by surgery alone, and on...

Challenges in artificial intelligence for polyp detection.

Weakly supervised end-to-end artificial intelligence in gastrointestinal endoscopy.

Artificial intelligence (AI) is widely used to analyze gastrointestinal (GI) endoscopy image data. A...

Diagnostic Accuracy of Wireless Capsule Endoscopy in Polyp Recognition Using Deep Learning: A Meta-Analysis.

AIM: As the completed studies have small sample sizes and different algorithms, a meta-analysis was ...

Dual resolution deep learning network with self-attention mechanism for classification and localisation of colorectal cancer in histopathological images.

AIMS: Microscopic examination is a basic diagnostic technology for colorectal cancer (CRC), but it i...

Applications of Artificial Intelligence in Screening, Diagnosis, Treatment, and Prognosis of Colorectal Cancer.

Colorectal cancer (CRC) is one of the most common cancers worldwide. Accurate early detection and di...

Deep learning radiomics based on contrast-enhanced ultrasound images for assisted diagnosis of pancreatic ductal adenocarcinoma and chronic pancreatitis.

BACKGROUND: Accurate and non-invasive diagnosis of pancreatic ductal adenocarcinoma (PDAC) and chron...

Graph-Based Region and Boundary Aggregation for Biomedical Image Segmentation.

Segmentation is a fundamental task in biomedical image analysis. Unlike the existing region-based de...

Comparison of robot-assisted and conventional laparoscopy for colorectal surgery for endometriosis: A prospective cohort study.

BACKGROUND: Our objective was to evaluate surgical outcomes of robotic compared to conventional lapa...

Human colorectal cancer tissue assessment using optical coherence tomography catheter and deep learning.

Optical coherence tomography (OCT) can differentiate normal colonic mucosa from neoplasia, potential...

Machine learning predicts cancer subtypes and progression from blood immune signatures.

Clinical adoption of immune checkpoint inhibitors in cancer management has highlighted the interconn...

Predicting Colorectal Cancer Using Residual Deep Learning with Nursing Care.

Presently, colorectal cancer is the second most dangerous cancer; around 13% of people have been aff...