Colon Cancer

Transformers for colorectal cancer segmentation in CT imaging.

PURPOSE: Most recently transformer models became the state of the art in various medical image segme...

Early Postoperative Prediction of Complications and Readmission After Colorectal Cancer Surgery Using an Artificial Neural Network.

BACKGROUND: Early predictors of postoperative complications can risk-stratify patients undergoing co...

Deep Learning-Based Real-Time Ureter Identification in Laparoscopic Colorectal Surgery.

BACKGROUND: Iatrogenic ureteral injury is a serious complication of abdominopelvic surgery. Identify...

Deep learning classification of ex vivo human colon tissues using spectroscopic optical coherence tomography.

Screening for colorectal cancer (CRC) with colonoscopy has improved patient outcomes; however, it re...

A commentary on 'A CT-based multitask deep learning model for predicting tumor stroma ratio and treatment outcomes in patients with colorectal cancer: a multicenter cohort study'.

Morphometric analysis and tortuosity typing of the large intestine segments on computed tomography colonography with artificial intelligence.

BACKGROUND: Morphological properties such as length and tortuosity of the large intestine segments p...

GLGFormer: Global Local Guidance Network for Mucosal Lesion Segmentation in Gastrointestinal Endoscopy Images.

Automatic mucosal lesion segmentation is a critical component in computer-aided clinical support sys...

Integrated multi-omics analysis and machine learning to refine molecular subtypes, prognosis, and immunotherapy in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) has a malignant characteristic that is highly aggressive and prone to met...

Appropriate trust in artificial intelligence for the optical diagnosis of colorectal polyps: the role of human/artificial intelligence interaction.

BACKGROUND AND AIMS: Computer-aided diagnosis (CADx) for the optical diagnosis of colorectal polyps ...

Development of high-quality artificial intelligence for computer-aided diagnosis in determining subtypes of colorectal cancer.

BACKGROUND AND AIM: There are no previous studies in which computer-aided diagnosis (CAD) diagnosed ...

An artificial intelligence-designed predictive calculator of conversion from minimally invasive to open colectomy in colon cancer.

Minimally invasive surgery is safe and effective in colorectal cancer. Conversion to open surgery ma...

Fluorescence excitation-scanning hyperspectral imaging with scalable 2D-3D deep learning framework for colorectal cancer detection.

Colorectal cancer is one of the top contributors to cancer-related deaths in the United States, with...

Evaluating the prognostic value of tumor deposits in non-metastatic lymph node-positive colon adenocarcinoma using Cox regression and machine learning.

BACKGROUND: The 8th AJCC TNM staging for non-metastatic lymph node-positive colon adenocarcinoma pat...

Smartphone application for artificial intelligence-based evaluation of stool state during bowel preparation before colonoscopy.

OBJECTIVES: Colonoscopy (CS) is an important screening method for the early detection and removal of...

Enhancing the diagnostic accuracy of colorectal cancer through the integration of serum tumor markers and hematological indicators with machine learning algorithms.

BACKGROUND: Colorectal cancer has a high incidence and mortality rate due to a low rate of early dia...

Using diffusion models to generate synthetic labeled data for medical image segmentation.

PURPOSE: Medical image analysis has become a prominent area where machine learning has been applied....

Robust and consistent biomarker candidates identification by a machine learning approach applied to pancreatic ductal adenocarcinoma metastasis.

BACKGROUND: Machine Learning (ML) plays a crucial role in biomedical research. Nevertheless, it stil...

Communicative competence of generative artificial intelligence in responding to patient queries about colorectal cancer surgery.

PURPOSE: To examine the ability of generative artificial intelligence (GAI) to answer patients' ques...

Testing Machine Learning Models to Predict Postoperative Ileus after Colorectal Surgery.

Postoperative ileus (POI) is a common complication after colorectal surgery, leading to increased h...

Ultrasensitive plasma-based monitoring of tumor burden using machine-learning-guided signal enrichment.

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate ...

IU-Net: A dual-path U-Net with rich information interaction for medical image segmentation.

Although the U-shape networks have achieved remarkable performances in many medical image segmentati...