Colon Cancer

Identification of DNA damage response and crotonylation-related biomarkers for lung adenocarcinoma via machine learning and WGCNA.

DNA damage response (DDR) and crotonylation occur frequently in lung adenocarcinoma (LUAD), but thei...

Comprehensive analysis of cholesterol metabolism-related genes in prostate cancer: integrated analysis of single-cell and bulk RNA sequencing.

BACKGROUND: Cholesterol metabolism plays a significant role in cancer progression, including prostat...

Deep learning neural network of adenocarcinoma detection in effusion cytology.

OBJECTIVE: Cytologic examination, which confirms the presence or absence of malignant cells, detects...

Non-invasive breath testing to detect colorectal cancer: protocol for a multicentre, case-control development and validation study (COBRA2 study).

BACKGROUND: Colorectal cancer (CRC) is the fourth most common cancer in the United Kingdom. The five...

What Every Colorectal Surgeon Should Know About Artificial Intelligence.

Plasmonic Fiber Optic Sensing Platform for Point-of-Care Pharmacokinetic Monitoring of Platinum Chemotherapeutics: Toward Ultratrace Multi-omics Precision Chemotherapy Management.

Precision chemotherapy management requires efficient and ultrasensitive dynamic monitoring of drug p...

Advancements in lung cancer: molecular insights, innovative therapies, and future prospects.

Still among the most common and deadly cancers worldwide, lung cancer causes major morbidity and dea...

Fully automated 3D multi-modal deep learning model for preoperative T-stage prediction of colorectal cancer using F-FDG PET/CT.

PURPOSE: This study aimed to develop a fully automated 3D multi-modal deep learning model using preo...

A review on computer-aided diagnostic system to classify the disorders of the gastrointestinal tract.

Various diseases, such as colon cancer, gastric cancer, celiac, and bleeding, pose a significant ris...

Machine learning-based dynamic CEA trajectory and prognosis in gastric cancer.

BACKGROUND: Static carcinoembryonic antigen (CEA) levels are well‑established prognostic markers in ...

Eye Tracking Analysis to Determine the Endoscopist's Recognition Rate for Artificial Intelligence-Detected Sites in Colonoscopy.

PURPOSE: Computer-aided detection systems (CADe) are used in screening colonoscopy; however, no stud...

Minimal Ablative Margin Quantification Using Hepatic Arterial Versus Portal Venous Phase CT for Colorectal Metastases Segmentation: A Dual-center, Retrospective Analysis.

OBJECTIVE: To compare the predictive value of minimal ablative margin (MAM) quantification using tum...

Super Learner Enhances Postoperative Complication Prediction in Colorectal Surgery.

OBJECTIVE: To determine if a Super Learner (SL) machine learning approach could improve the predicti...

Prospective multicenter validation of a machine learning model for predicting anastomotic leakage in patients with gastric adenocarcinoma undergoing total or proximal gastrectomy.

OBJECTIVE: Predicting esophago-gastric and esophagojejunal anastomotic leakage (AL) is inherently ch...

Ferroptosis-disulfidptosis-related CHMP6 is a clinico-immune target in colorectal cancer.

BACKGROUND: Ferroptosis and disulfidptosis are newly discovered forms of regulated cell death that p...

Nanopore full length 16S rRNA gene sequencing increases species resolution in bacterial biomarker discovery.

Discovery of disease-related bacterial biomarkers could be a useful approach for early prevention or...

Colorectal Polyp Size Measurement Faces Infinite Possibilities: Artificial Intelligence Is the Key.

BACKGROUND: Colorectal neoplasia poses a severe health threat worldwide. The accurate measurement of...

Establishment of two pathomic-based machine learning models to predict CLCA1 expression in colon adenocarcinoma.

Chloride channel accessory 1 (CLCA1) is considered a potential prognostic biomarker for colon adenoc...

Systematic review and meta-analysis of deep learning for MSI-H in colorectal cancer whole slide images.

This meta-analysis evaluated diagnostic performance of deep learning (DL) algorithms using whole sli...

Integrative multi-omics and machine learning reveal critical functions of proliferating cells in prognosis and personalized treatment of lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is a major cause of cancer-related mortality globally. Proliferating cell...

Performance of Machine Learning in Diagnosing KRAS (Kirsten Rat Sarcoma) Mutations in Colorectal Cancer: Systematic Review and Meta-Analysis.

BACKGROUND: With the widespread application of machine learning (ML) in the diagnosis and treatment ...