Colon Cancer

Evaluation of an Artificial Intelligence-Augmented Digital System for Histologic Classification of Colorectal Polyps.

IMPORTANCE: Colorectal polyps are common, and their histopathologic classification is used in the pl...

Deep Learning and Pathomics Analyses Reveal Cell Nuclei as Important Features for Mutation Prediction of BRAF-Mutated Melanomas.

Image-based analysis as a method for mutation detection can be advantageous in settings when tumor t...

Deep Learning CT-based Quantitative Visualization Tool for Liver Volume Estimation: Defining Normal and Hepatomegaly.

Background Imaging assessment for hepatomegaly is not well defined and currently uses suboptimal, un...

BH-index: A predictive system based on serum biomarkers and ensemble learning for early colorectal cancer diagnosis in mass screening.

BACKGROUND AND OBJECTIVE: Colorectal cancer is one of the most common malignancies among the general...

Development and validation of a weakly supervised deep learning framework to predict the status of molecular pathways and key mutations in colorectal cancer from routine histology images: a retrospective study.

BACKGROUND: Determining the status of molecular pathways and key mutations in colorectal cancer is c...

Deep learning radiomics of dual-energy computed tomography for predicting lymph node metastases of pancreatic ductal adenocarcinoma.

PURPOSE: Diagnosis of lymph node metastasis (LNM) is critical for patients with pancreatic ductal ad...

Deep learning can predict lymph node status directly from histology in colorectal cancer.

BACKGROUND: Lymph node status is a prognostic marker and strongly influences therapeutic decisions i...

Systemic inflammatory response in robot-assisted and laparoscopic surgery for colon cancer (SIRIRALS): study protocol of a randomized controlled trial.

BACKGROUND: Robot-assisted surgery is being increasingly adopted in treating colorectal cancer, and ...

CST: A Multitask Learning Framework for Colorectal Cancer Region Mining Based on Transformer.

Colorectal cancer is a high death rate cancer until now; from the clinical view, the diagnosis of th...

A Deep Learning Approach for Colonoscopy Pathology WSI Analysis: Accurate Segmentation and Classification.

Colorectal cancer (CRC) is one of the most life-threatening malignancies. Colonoscopy pathology exam...

Mutual-Prototype Adaptation for Cross-Domain Polyp Segmentation.

Accurate segmentation of the polyps from colonoscopy images provides useful information for the diag...

3D multi-scale, multi-task, and multi-label deep learning for prediction of lymph node metastasis in T1 lung adenocarcinoma patients' CT images.

The diagnosis of preoperative lymph node (LN) metastasis is crucial to evaluate possible therapy opt...

Pancreatic Cancer Survival Prediction: A Survey of the State-of-the-Art.

Cancer early detection increases the chances of survival. Some cancer types, like pancreatic cancer,...

Artificial intelligence for pre-operative lymph node staging in colorectal cancer: a systematic review and meta-analysis.

BACKGROUND: Artificial intelligence (AI) is increasingly being used in medical imaging analysis. We ...

Identification of clinical trait-related small RNA biomarkers with weighted gene co-expression network analysis for personalized medicine in endocervical adenocarcinoma.

Endocervical adenocarcinoma (EAC) is an aggressive type of endocervical cancer. At present, molecula...

Distinguishing pure histopathological growth patterns of colorectal liver metastases on CT using deep learning and radiomics: a pilot study.

Histopathological growth patterns (HGPs) are independent prognosticators for colorectal liver metast...

Multi-step validation of a deep learning-based system for the quantification of bowel preparation: a prospective, observational study.

BACKGROUND: Inadequate bowel preparation is associated with a decrease in adenoma detection rate (AD...

Deep learning for automated bowel preparation assessment during colonoscopy: time to embrace a new approach?

functional cell phenotyping reveals microdomain networks in colorectal cancer recurrence.

Tumors are dynamic ecosystems comprising localized niches (microdomains), possessing distinct compos...

Personalised Medicine for Colorectal Cancer Using Mechanism-Based Machine Learning Models.

Gaining insight into the mechanisms of signal transduction networks (STNs) by using critical feature...

Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial).

BACKGROUND & AIMS: Artificial intelligence-based computer-aided polyp detection (CADe) systems are i...