Colon Cancer

Comparison and fusion prediction model for lung adenocarcinoma with micropapillary and solid pattern using clinicoradiographic, radiomics and deep learning features.

To investigate whether the combination scheme of deep learning score (DL-score) and radiomics can im...

Sources of performance variability in deep learning-based polyp detection.

PURPOSE: Validation metrics are a key prerequisite for the reliable tracking of scientific progress ...

MM-GLCM-CNN: A multi-scale and multi-level based GLCM-CNN for polyp classification.

Distinguishing malignant from benign lesions has significant clinical impacts on both early detectio...

Commentary on 'Effectiveness of artificial intelligence-assisted colonoscopy in early diagnosis of colorectal cancer: a systematic review'.

Machine learning for predicting survival of colorectal cancer patients.

Colorectal cancer is one of the most incident types of cancer in the world, with almost 2 million ne...

Ensemble-based multi-tissue classification approach of colorectal cancer histology images using a novel hybrid deep learning framework.

Colorectal cancer (CRC) is the second leading cause of cancer death in the world, so digital patholo...

Fully Automated Tumor Bud Assessment in Hematoxylin and Eosin-Stained Whole Slide Images of Colorectal Cancer.

Tumor budding (TB), the presence of single cells or small clusters of up to 4 tumor cells at the inv...

Right hemicolectomy for ascending colon cancer using the hinotori surgical robot system: The first ever case report for colon cancer.

The hinotori Surgical Robot System obtained pharmaceutical approval for use in colorectal cancer sur...

Domain-specific transfer learning in the automated scoring of tumor-stroma ratio from histopathological images of colorectal cancer.

Tumor-stroma ratio (TSR) is a prognostic factor for many types of solid tumors. In this study, we pr...

Deep learning for multi-class semantic segmentation enables colorectal cancer detection and classification in digital pathology images.

In colorectal cancer (CRC), artificial intelligence (AI) can alleviate the laborious task of charact...

Artificial intelligence in intestinal polyp and colorectal cancer prediction.

Artificial intelligence (AI) algorithms and their application to disease detection and decision supp...

ChatGPT and Patient Questions About Colonoscopy: Comment.

Outcomes of robot-assisted versus laparoscopic surgery for colorectal cancer in morbidly obese patients: A propensity score-matched analysis of the US Nationwide Inpatient Sample.

BACKGROUND AND AIM: Morbid obesity is associated with poorer postoperative outcomes in colorectal ca...

ChatGPT in Colorectal Surgery: A Promising Tool or a Passing Fad?

Colorectal surgery is a specialized branch of surgery that involves the diagnosis and treatment of c...

A trial deep learning-based model for four-class histologic classification of colonic tumor from narrow band imaging.

Narrow band imaging (NBI) has been extensively utilized as a diagnostic tool for colorectal neoplast...

An Investigation about Modern Deep Learning Strategies for Colon Carcinoma Grading.

Developing computer-aided approaches for cancer diagnosis and grading is currently receiving an incr...

Dual-feature Fusion Attention Network for Small Object Segmentation.

Accurate segmentation of medical images is an important step during radiotherapy planning and clinic...

Preliminary evaluation of deep learning for first-line diagnostic prediction of tumor mutational status.

The detection of tumour gene mutations by DNA or RNA sequencing is crucial for the prescription of e...

Machine Learning Predicts the Oxidative Stress Subtypes Provide an Innovative Insight into Colorectal Cancer.

So far, it has been reached the academic consensus that the molecular subtypes are via genomic heter...

BCU-Net: Bridging ConvNeXt and U-Net for medical image segmentation.

Medical image segmentation enables doctors to observe lesion regions better and make accurate diagno...

Automated classification of polyps using deep learning architectures and few-shot learning.

BACKGROUND: Colorectal cancer is a leading cause of cancer-related deaths worldwide. The best method...