Colon Cancer

Management and outcomes of brain metastases from pancreatic adenocarcinoma: a pooled analysis and literature review.

BACKGROUND: Brain metastases (BM) are rare in pancreatic ductal adenocarcinoma (PDAC) and little dat...

CT-Based Super-Resolution Deep Learning Models with Attention Mechanisms for Predicting Spread Through Air Spaces of Solid or Part-Solid Lung Adenocarcinoma.

RATIONALE AND OBJECTIVES: Spread through air space (STAS) is a novel invasive pattern of lung adenoc...

Social network analysis of cell networks improves deep learning for prediction of molecular pathways and key mutations in colorectal cancer.

Colorectal cancer (CRC) is a primary global health concern, and identifying the molecular pathways, ...

Efficacy of artificial intelligence in reducing miss rates of GI adenomas, polyps, and sessile serrated lesions: a meta-analysis of randomized controlled trials.

BACKGROUND AND AIMS: The aim of this study was to determine if utilization of artificial intelligenc...

Immune, metabolic landscapes of prognostic signatures for lung adenocarcinoma based on a novel deep learning framework.

Lung adenocarcinoma (LUAD) is a malignant tumor with high lethality, and the aim of this study was t...

Deep learning system for true- and pseudo-invasion in colorectal polyps.

Over 15 million colonoscopies were performed yearly in North America, during which biopsies were tak...

From Staining Techniques to Artificial Intelligence: A Review of Colorectal Polyps Characterization.

This review article provides a comprehensive overview of the evolving techniques in image-enhanced e...

Prediction of early-onset colorectal cancer mortality rates in the United States using machine learning.

INTRODUCTION: The current study, focusing on a significant US (United States) colorectal cancer (CRC...

CRPU-NET: a deep learning model based semantic segmentation for the detection of colorectal polyp in lower gastrointestinal tract.

. The objectives of the proposed work are twofold. Firstly, to develop a specialized light weight CR...

A Cohort Study Investigating Zearalenone Concentrations and Selected Steroid Levels in Patients with Sigmoid Colorectal Cancer or Colorectal Cancer.

THE AIM: In this study was to determine if sigmoid colorectal cancer (SCC) and colorectal cancer (CR...

Current implications and challenges of artificial intelligence technologies in therapeutic intervention of colorectal cancer.

Irrespective of men and women, colorectal cancer (CRC), is the third most common cancer in the popul...

AN ELECTRONIC MEDICAL RECORD PREDICTION MODEL TO IDENTIFY INADEQUATE BOWEL PREPARATION IN PATIENTS AT OUTPATIENT COLONOSCOPY.

BACKGROUND AND AIMS: Inadequate bowel preparation during colonoscopy is associated with decreased ad...

Towards Semi-Autonomous Colon Screening Using an Electromagnetically Actuated Soft-Tethered Colonoscope Based on Visual Servo Control.

OBJECTIVE: Conventional colonoscopy using a flexible colonoscope remains two major limitations, incl...

Albumin-Bilirubin (ALBI) Score and Systemic Immune-Inflammation Indexes Used As Pretreatment Outcome Predictors in Patients With Pancreatic Ductal Adenocarcinoma Undergoing Robotic or Open Whipple Procedures: A Logistic Regression Analysis.

Background Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer (PC)...

Diagnostic accuracy of endocytoscopy via artificial intelligence in colorectal lesions: A systematic review and meta‑analysis.

BACKGROUND: Endocytoscopy (EC) is a nuclei and micro-vessels visualization in real-time and can faci...

Development and validation of a three-dimensional deep learning-based system for assessing bowel preparation on colonoscopy video.

BACKGROUND: The performance of existing image-based training models in evaluating bowel preparation ...

Enhancing artificial intelligence-doctor collaboration for computer-aided diagnosis in colonoscopy through improved digital literacy.

Establishing appropriate trust and maintaining a balanced reliance on digital resources are vital fo...

Secret learning for lung cancer diagnosis-a study with homomorphic encryption, texture analysis and deep learning.

Advanced lung cancer diagnoses from radiographic images include automated detection of lung cancer f...

Deep learning models for automatic tumor segmentation and total tumor volume assessment in patients with colorectal liver metastases.

BACKGROUND: We developed models for tumor segmentation to automate the assessment of total tumor vol...

Colonoscopy setting and impact on statistical significance in Artificial Intelligence trials.

Cancer care pathways across seven countries in Europe: What are the current obstacles? And how can artificial intelligence help?

BACKGROUND: Cancer poses significant challenges for healthcare professionals across the disease path...