Colon Cancer

Machine-learning and scRNA-Seq-based diagnostic and prognostic models illustrating survival and therapy response of lung adenocarcinoma.

Lung cancer is a major cause accounting for cancer-related mortalities, with lung adenocarcinoma (LU...

BMCS-Net: A Bi-directional multi-scale cascaded segmentation network based on transformer-guided feature Aggregation for medical images.

convolutional neural networks (CNNs) show great potential in medical image segmentation tasks, and c...

RACGAP1 is a pivotal gene in lung adenocarcinoma-associated membranous nephropathy: Based on comprehensive bioinformatics analysis and machine learning.

BACKGROUND: This study performs a detailed bioinformatics and machine learning analysis to investiga...

Clinical-Grade Validation of an Autofluorescence Virtual Staining System With Human Experts and a Deep Learning System for Prostate Cancer.

The tissue diagnosis of adenocarcinoma and intraductal carcinoma of the prostate includes Gleason gr...

Endoscopic Artificial Intelligence for Image Analysis in Gastrointestinal Neoplasms.

BACKGROUND: Artificial intelligence (AI) using deep learning systems has recently been utilized in v...

Machine learning and bioinformatics analysis of diagnostic biomarkers associated with the occurrence and development of lung adenocarcinoma.

OBJECTIVE: Lung adenocarcinoma poses a major global health challenge and is a leading cause of cance...

A Boundary-Enhanced Decouple Fusion Segmentation Network for Diagnosis of Adenomatous Polyps.

Adenomatous polyps, a common premalignant lesion, are often classified into villous adenoma (VA) and...

AI-driven automatic compression system for colorectal anastomosis.

Although circular staplers offer technical advancements over traditional hand-sewn techniques, their...

An artificial intelligence-assisted system versus white light endoscopy alone for adenoma detection in individuals with Lynch syndrome (TIMELY): an international, multicentre, randomised controlled trial.

BACKGROUND: Computer-aided detection (CADe) systems for colonoscopy have been shown to increase smal...

Artificial intelligence-based plasma exosome label-free SERS profiling strategy for early lung cancer detection.

As a lung cancer biomarker, exosomes were utilized for in vitro diagnosis to overcome the lack of se...

Lymph node metastasis detection using artificial intelligence in T1 colorectal cancer: A comprehensive systematic review.

We systematically reviewed the application of artificial intelligence (AI) in predicting lymph node ...

A depth analysis of recent innovations in non-invasive techniques using artificial intelligence approach for cancer prediction.

The fight against cancer, a relentless global health crisis, emphasizes the urgency for efficient an...

Artificial intelligence in colorectal multidisciplinary team meetings. What are the medicolegal implications?

AIM: To give an insight into areas for future development and suggestions in the complexities of inc...

Novel Artificial Intelligence Combining Convolutional Neural Network and Support Vector Machine to Predict Colorectal Cancer Prognosis and Mutational Signatures From Hematoxylin and Eosin Images.

Reducing recurrence following radical resection of colon cancer without overtreatment or undertreatm...

Developing a machine learning-based prognosis and immunotherapeutic response signature in colorectal cancer: insights from ferroptosis, fatty acid dynamics, and the tumor microenvironment.

INSTRUCTION: Colorectal cancer (CRC) poses a challenge to public health and is characterized by a hi...

Efficient multi-stage feedback attention for diverse lesion in cancer image segmentation.

In the domain of Computer-Aided Diagnosis (CAD) systems, the accurate identification of cancer lesio...

Lung Adenocarcinoma Systems Biomarker and Drug Candidates Identified by Machine Learning, Gene Expression Data, and Integrative Bioinformatics Pipeline.

Lung adenocarcinoma (LUAD) is a significant planetary health challenge with its high morbidity and m...

Combined expert-in-the-loop-random forest multiclass segmentation U-net based artificial intelligence model: evaluation of non-small cell lung cancer in fibrotic and non-fibrotic microenvironments.

BACKGROUND: The tumor microenvironment (TME) plays a key role in lung cancer initiation, proliferati...

Pioneering noninvasive colorectal cancer detection with an AI-enhanced breath volatilomics platform.

The sensitivity and specificity of current breath biomarkers are often inadequate for effective can...

CHNet: A multi-task global-local Collaborative Hybrid Network for KRAS mutation status prediction in colorectal cancer.

Accurate prediction of Kirsten rat sarcoma (KRAS) mutation status is crucial for personalized treatm...

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