Colon Cancer

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

The association between obesity and cancer risk carries substantial public health ramifications as obesity promotes cancer advancement via many cellular and molecular mechanisms. This study utilizes Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and narrative systematic review guidelines to evaluate 221 research articles selected from an initial collection of 1,288 pub...

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 global health challenges. While the mitochondrial unfolded protein response (UPR) is known to influence cancer biology, its specific role in CESC remains unclear.

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 prognostic. A deep-learning segmentation model for CRLM ...

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 (CECT) radiomics features with clinicopathologica...

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 molecular docking, are often limited by empirical scorin...

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

Computer-aided diagnosis (CADx) in colonoscopy aims to improve the accuracy of diagnosing small polyps; however, its integration into clinical practic...

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 feature interaction-guided fusion (DL-MFIF) framework t...

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). Precise identification of IgG subclass-specific g...

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, with early postoperative recurrence remaining a ma...

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 early detection remains challenging due to the lack...

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 responsiveness to immunotherapy due to its predomin...

Quantum machine learning-based electrokinetic mining for the identification of nanoparticles and exosomes with minimal training data.

Synthetic and naturally occurring particles, such as nanoparticles (NPs) and exosomes; a type of extracellular vesicles (EVs), have garnered widesprea...

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

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of cancer-related mortality globally, with many patients diagnosed at advanced stages. Cur...

ÆMMamba: An Efficient Medical Segmentation Model With Edge Enhancement.

Medical image segmentation is critical for disease diagnosis, treatment planning, and prognosis assessment, yet the complexity and diversity of medica...

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 adenocarcinoma (LUAD) being the most common subtype. Ar...

Towards automating risk stratification of intraductal papillary mucinous Neoplasms: Artificial intelligence advances beyond human expertise with confocal laser endomicroscopy.

BACKGROUND AND AIMS: Endoscopic Ultrasound (EUS)-guided needle-based confocal laser endomicroscopy (nCLE) enables real-time microscopic visualization ...

Microbial vitamin biosynthesis links gut microbiota dynamics to chemotherapy toxicity.

Dose-limiting toxicities pose a major barrier to cancer treatment. While preclinical studies show that the gut microbiota influences and is influenced...

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 repair deficiency (dMMR) in colorectal carcinoma (CRC)....

Future of image enhanced endoscopy of esophageal adenocarcinoma.

Barrett's esophagus is a premalignant precursor lesion of esophageal adenocarcinoma that affects approximately 1% of the population worldwide. Esophag...

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, emphasizing the critical need for the accurate class...