Colon Cancer

Performance of large language models in addressing patient queries on colorectal cancer screening in different languages: An international study across 28 countries.

BACKGROUND: Colorectal cancer (CRC) screening reduces incidence and mortality, yet patient adherence remains suboptimal. Large language models may improve participation by addressing patient questions in native languages, but their multilingual performance has not been systematically assessed. METHODS: From April to June 2025, we conducted a cross-continental study involving 28 countries and 23 la...

Artificial Intelligence in Colorectal Cancer Supportive Care: A Scoping Review.

PURPOSE: Artificial Intelligence (AI) has the potential to enhance supportive care for cancer survivors from diagnosis through treatment and into survivorship. This study aimed to provide an overview of available evidence on AI applications in supportive care for individuals with colorectal cancer (CRC). METHODS: This scoping review was conducted following the Joanna Briggs Institute guidelines. S...

Multi-modal sensing in colonoscopy: a data-driven approach.

Soft optical sensors hold potential for enhancing minimally invasive procedures like colonoscopy, yet their complex, multi-modal responses pose signif...

Primary tissue metabolic fingerprinting for efficient diagnosis of lymph node metastasis and metabolic reprogramming mechanisms in colorectal cancer.

Accurate detection of lymph node metastasis (LNM) is critical for colorectal cancer (CRC) staging and treatment planning, yet current histopathologica...

Bayesian selection of lipidome dynamics features for a K-nearest neighbors (KNN) classifier model of tumor response in patients with advanced gastrointestinal adenocarcinoma undergoing systemic treatment.

BACKGROUND: Dysregulated lipid metabolism is common in patients with gastrointestinal (GI) cancer. This study investigated the ability of plasma lipid...

A hybrid framework integrating serum biochemical markers and FTIR spectroscopy with machine learning for early cancer screening.

Early detection of cancer remains a key challenge in clinical diagnosis. This study explored two serum sample-based early cancer screening methods: on...

The basis for future personalized therapy approaches - Machine learning-generated 1-year survival rate, metastatic status and therapy-dependent survival in pancreatic cancer patients.

BACKGROUND: Pancreatic adenocarcinoma (PDAC) remains one of the most lethal types of cancer, characterized by its unspecific symptoms, aggressive natu...

Explainable machine learning model for predicting early recurrence and distant metastasis after surgery in early-onset colorectal cancer.

OBJECTIVE: To develop explainable machine learning models for predicting the risk of early postoperative recurrence and distant metastasis in patients...

Artificial intelligence takes on the multidisciplinary committee: A single-center study for rectal cancer management.

BACKGROUND: As rectal cancer management evolves, the multidisciplinary committee becomes increasingly important in integrating expertise to optimize p...

Modulating tumor mechanics and vascular barriers to enhance chemotherapy efficacy in pancreatic tumors and melanoma.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense stroma and dysfunctional vasculature, limiting drug delivery and immune infiltrati...

Interpretable fusion deep learning on super-resolution MRI for perineural invasion prediction in pancreatic ductal adenocarcinoma: a multicenter study.

PURPOSE: To develop an interpretable fusion deep learning model based on super-resolution (SR) MRI for predicting preoperative perineural invasion (PN...

Integrative bioinformatics analysis reveals that microplastics promote chronic rhinosinusitis with nasal polyps through NOXO1-mediated oxidative stress and myoepithelial cell reprogramming.

Chronic rhinosinusitis with nasal polyps (CRSwNP) is a complex inflammatory disease whose environmental pathogenic factors remain unclear. Microplasti...

Interpreting Deep Learning-Based Prediction of the BRAF V600E Mutation Using Diagnostic Whole Slide Images in Skin Cutaneous Melanoma.

Deep learning (DL) models have shown promise in predicting molecular alterations directly from hematoxylin and eosin-stained whole slide images in a v...

Circadian rhythm: An emerging force for colorectal cancer treatment.

The relationship between circadian rhythm disorder and the occurrence and progression of colorectal cancer (CRC) has received attention. The circadian...

Emerging nanoparticle-based therapies for pancreatic cancer: Current clinical landscape.

Pancreatic cancer, particularly ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal subtypes due to late diagnosis, the absence of e...

Allosteric prediction via convolutional neural networks and protein structural and dynamical features.

Allostery is the phenomenon whereby a binding event or covalent modification at one site in a protein modulates function at a distal site, thus changi...

Preoperative Identification of Lymph Node Metastasis in Colorectal Cancer Using Noninvasive Circulating Tumor DNA Methylation Signatures: Results From a Prospective Study.

BACKGROUND: Lymph node metastasis is important for the management and surgical procedures of patients with colorectal cancer. Preoperative identificat...

MethylMSI: Prediction of microsatellite instability based on DNA methylation profile and SVM model.

Microsatellite instability (MSI) has gained increasing attention as a promising biomarker for cancer immunotherapy in diverse cancer types. As a resul...

An Exosome-Based Liquid Biopsy for the Detection of Early-Onset Colorectal Cancer: The ENCODER Multicenter Study.

BACKGROUND & AIMS: The incidence of early-onset colorectal cancer (EOCRC; diagnosed before age 50 years) continues to increase, now standing as the le...

Alternative splicing in cancer drug resistance: Mechanisms and therapeutic prospects (Review).

Alternative splicing (AS) is one of the principal mechanisms of post‑transcriptional regulation that confers transcriptomic plasticity and proteomic d...