Colon Cancer

Large language models for detecting colorectal polyps in endoscopic images.

Evaluation of a deep-learning segmentation model for patients with colorectal cancer liver metastases (COALA) in the radiological workflow.

OBJECTIVES: For patients with colorectal liver metastases (CRLM), total tumor volume (TTV) is progno...

Machine learning explores the prognostic and immuno-oncological impact of mitochondrial unfolded protein response in CESC.

BACKGROUND: Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) pose significant...

Mechanisms underlying obesity-malignancy connection: a systematic narrative review.

The association between obesity and cancer risk carries substantial public health ramifications as o...

Guideline-driven clinical decision support for colonoscopy patients using the hierarchical multi-label deep learning method.

BACKGROUND: Over 20 million colonoscopies are performed in China annually. An automatic clinical dec...

Graph convolutional neural networks improved target-specific scoring functions for cGAS and kRAS in virtual screening.

In the drug discovery process, traditional structure-based virtual screening methods, such as molecu...

Interpretable machine learning model integrating contrast-enhanced CT environmental radiomics and clinicopathological features for predicting postoperative recurrence in lung adenocarcinoma: a retrospective pilot study.

PURPOSE: This study aims to develop an interpretable predictive model combining contrast-enhanced CT...

Plasma and Urine Circulating Tumor DNA Methylation Profiles for Non-Invasive Pancreatic Ductal Adenocarcinoma Detection: Significant Findings in Plasma Only.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with limited treatment options, and e...

Interpretable machine learning models based on body composition and inflammatory nutritional index (BCINI) to predict early postoperative recurrence of colorectal cancer: Multi-center study.

BACKGROUND AND OBJECTIVE: Colorectal cancer (CRC) ranks among the most prevalent cancers worldwide, ...

A robust label-free workflow for the immunoglobulin G subclass site-specific N-glycopeptides and the glycosylation of IgG 2 correlated with colorectal cancer.

Immunoglobulin G (IgG) subclasses glycosylation reflects the progression of colorectal cancer (CRC)....

Deep Learning-Based Multimodal Feature Interaction-Guided Fusion: Enhancing the Evaluation of EGFR in Advanced Lung Adenocarcinoma.

RATIONALE AND OBJECTIVES: The aim of this study is to develop a deep learning-based multimodal featu...

Computer-aided diagnosis of colorectal polyps: assisted or autonomous?

Computer-aided diagnosis (CADx) in colonoscopy aims to improve the accuracy of diagnosing small poly...

Single-cell and bulk transcriptome analyses reveal elevated amino acid metabolism promoting tumor-directed immune evasion in colorectal cancer.

INTRODUCTION: Colorectal cancer (CRC), the third most common cancer worldwide, often shows limited r...

Arginine methylation patterns in LUAD: defining prognostic subtypes and relevance to immunotherapy.

BACKGROUND: Lung cancer remains the leading cause of cancer-related death worldwide, with lung adeno...

ÆMMamba: An Efficient Medical Segmentation Model With Edge Enhancement.

Medical image segmentation is critical for disease diagnosis, treatment planning, and prognosis asse...

Computational analysis of DEHP's oncogenic role in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of cancer-related mortality globally, wi...

Microbial vitamin biosynthesis links gut microbiota dynamics to chemotherapy toxicity.

Dose-limiting toxicities pose a major barrier to cancer treatment. While preclinical studies show th...

Multiclassification of Colorectal Polyps from Colonoscopy Images Using AI for Early Diagnosis.

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide, em...

Future of image enhanced endoscopy of esophageal adenocarcinoma.

Barrett's esophagus is a premalignant precursor lesion of esophageal adenocarcinoma that affects app...

Deep learning predicts microsatellite instability status in colorectal carcinoma in an ethnically heterogeneous population in South Africa.

BACKGROUND: Deep learning (DL) models are effective pre-screening tools for detecting mismatch repai...

Classification of non-small cell lung cancer by histologic subtype using deep learning in public and private data sets of computed tomography images.

OBJECTIVE: To develop a deep learning system to classify non-small cell lung cancer (NSCLC) by histo...