Colon Cancer

Lung cancer as a global health challenge: Multidimensional biomarker research and therapeutic advances.

Lung cancer, the leading cause of global cancer-related mortality, is categorized into small-cell and non-small-cell subtypes. The heterogeneous non-small-cell lung cancer group is further subcategorized primarily into adenocarcinoma, squamous cell carcinoma, and large cell carcinoma, each underpinned by distinct molecular alterations. Although traditional serum biomarkers aid in subtype different...

Automated Flow and local LLM-Driven clinical Context Engineering: Precision colorectal cancer recurrence registry.

OBJECTIVE: This study develops and validates a deployable, privacy-preserving automated tool to address the labor-intensive nature of colorectal cancer (CRC) recurrence registration. Our tool utilizes a reproducible, two-stage 'Clinical Context Engineering' workflow to mimic expert clinical reasoning and overcome the limitations of handling longitudinal clinical data ambiguity. METHODS: We retrosp...

Advancements in Screening Strategies for Early-Onset Colorectal Cancer (EOCRC).

Screening for early-onset colorectal cancer is a growing public health concern, driven by a rising incidence in younger adults. As trends shift, scree...

A comprehensive European Colorectal Cancer Cohort dataset.

Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. The Biobanking and Biomolecular Resources European Research Infrastruct...

AI caption generation model for digital pathology of adenocarcinoma in endoscopic histopathology using multi-instance attention mechanisms.

Detection of Lung and Colon Cancer Using XRx-Net With Histopathological Images.

Lung and Colon Cancer (LCC) is a prevalent type of cancer influenced by factors such as genetics, smoking, second-hand smoke exposure, and alcohol con...

Downregulated lysyl oxidase in plasma extracellular vesicles: a biomarker linked to brain metastasis risk in lung adenocarcinoma.

BACKGROUND: Brain metastasis (BrM) is a leading cause of mortality in patients with lung adenocarcinoma (LUAD). Extracellular vesicles (EVs), which ca...

RAS signaling in lung adenocarcinoma is defined by lineage context and DUSP4 loss.

BACKGROUND: The molecular landscape of lung adenocarcinoma (LUAD) is often illustrated as a driver-oncogene "pie chart," but identical mutations exhib...

Multiclass Radiomics-Based Prediction of BRAF Mutation Status in Pediatric Low-Grade Gliomas Using Multisequence MRI.

BACKGROUND AND PURPOSE: Pediatric low-grade gliomas (pLGGs) are the most common brain tumors in children and frequently harbor BRAF alterations, most ...

Mathematical fidelity vs. perceptual realism: A multi-center study of super-resolution radiomics for lung adenocarcinoma invasiveness.

OBJECTIVE: To identify the optimal super-resolution (SR) architecture for radiomics by comparing three models (Residual Channel Attention Network (RCA...

BRAF inhibitor resistance in melanoma: from resistance mechanisms to therapeutic innovations.

BRAF inhibitors (BRAFi) have transformed the treatment of BRAF mutant melanoma, but inherent and acquired resistance remains a major barrier to curati...

PIBAdb: a public cohort of multimodal colonoscopy videos and images including polyps with histological information.

BACKGROUND AND OBJECTIVE: Colorectal cancer is the third most common cancer worldwide and presents a high mortality rate. Colonoscopy is the gold stan...

A lightweight CNN for enhanced non-small cell lung cancer classification using CT scan image.

Lung cancer is a leading cause of cancer-related mortality worldwide, and its early and accurate detection is critical for improving patient outcomes....

A targeted proteomics assay for the preoperative diagnosis of thyroid nodules.

Accurate preoperative diagnosis of thyroid nodules via fine-needle aspiration (FNA) biopsy remains challenging, particularly in cases with indetermina...

Assessment of quantum chemical predictors for anti-colorectal cancer agents using QSAR modeling.

Optimizing the prediction of anti-colorectal cancer agent activity is essential aspect in the identification and creation of medications. Machine lear...

Pathology Public Datasets for Artificial Intelligence: A Systematic Review.

Histopathology plays a crucial role in the diagnosis of many diseases, especially cancers, for which the correct classification of tissue samples sign...

CT radiomics of adenocarcinoma of the esophagogastric junction: machine learning-based prediction of perineural invasion status.

Effect of a Computer-Aided Device for Detecting Gastric Neoplasms: A Multicenter, Randomized Controlled Trial.

BACKGROUND & AIMS: Evidence about the effect of artificial intelligence (AI) on upper endoscopy in multicenter, randomized controlled trials is lackin...

Integrative network pharmacology and machine learning identify potential targets of indole-3-lactic acid in colorectal cancer.

The treatment of colorectal cancer (CRC) remains challenging due to chemotherapy resistance and genetic heterogeneity. Indole-3-lactic acid (ILA), a t...

Tumor burden in metastatic colorectal cancer quantified using deep learning models: Prognostic value and maintenance treatment benefit in the CAIRO3 trial.

INTRODUCTION: Total tumor number (TTN) and total tumor volume (TTV) reflect tumor burden and have been linked to outcomes in metastatic colorectal can...