Colon Cancer

Two-Step Ensemble Convolutional Neural Networks for Colonoscopic Biopsy Classification Resembling Pathologists' Process.

BACKGROUND: Colorectal cancer (CRC) is a leading cause of mortality worldwide, and early examination via colonoscopy is increasingly used to prevent CRC mortality. Recently, studies have attempted utilizing artificial intelligence for the classification of CRC. However, datasets were limited in these studies, and the limited number of findings resulting from these studies are not specific to cance...

Integrative machine learning reveals interplay between epithelial and endothelial cells elevates mixed heavy metal-related colorectal cancer risk.

Heavy metal contamination has become an emerging global health concern, yet the promoting effects of mixed heavy metal exposure on colorectal cancer risk remains poorly understood. In this study, plasma concentrations of 25 heavy metals were obtained from an in-house elemental database comprising both colorectal cancer patients and healthy controls, and exposure concentrations were then defined ba...

A comparative analysis of parametric, semiparametric and machine learning models for survival prediction.

BACKGROUND: Survival analysis is crucial in medical research. This study provides a comprehensive comparison of parametric, semi-parametric, and machi...

KIF23 in disease pathogenesis and its therapeutic and diagnostic potential.

BACKGROUND: Kinesin family member 23 (KIF23) is a microtubule-dependent motor protein essential for cytokinesis, organelle transport, and signaling pa...

An automatic detection model for spread through air spaces in postoperative pathological sections based on deep learning in NSCLC.

Spread through air spaces (STAS) is recognized as an aggressive pattern of invasion in lung cancer and has been associated with poorer survival outcom...

Integration of single-cell regulon atlas and bulk RNA-seq for individualized prognostic prediction in stomach adenocarcinoma.

Transcriptional regulators reflect cellular heterogeneity and are key for prognostic modeling. Given the poor prognosis of stomach adenocarcinoma (STA...

Y-Polyp: research on devices for detecting colorectal polyps with limited samples.

BACKGROUNDS: Colonoscopy plays a crucial role in preventing the malignant transformation of colorectal polyps, with early diagnosis and detection of c...

Survival prediction of colorectal cancer using 101 machine learning methods based on immune-related genes: A machine learning study.

Colorectal cancer (CRC) is characterized by high incidence and mortality rates. Early identification of high-risk CRC patients and timely intervention...

Virtual crystal violet chromoendoscopy: a digital alternative to dye-based staining.

BACKGROUND AND AIMS: Routine use of crystal violet (CV) chromoendoscopy for pit pattern-based colorectal lesion characterization is limited by safety ...

Global incidence patterns of early-onset gastrointestinal cancers and their ecological associations with behavioural risk factors.

BACKGROUND: Early-onset gastrointestinal cancers (EOGIC) are increasingly recognised as an urgent global health concern. We aimed to describe the glob...

Dual-attention bidirectional LSTM with feature genomic analysis improves prognostic survival prediction in colorectal cancer patients.

The increasing incidence and mortality rates of colorectal cancer necessitate accurate prediction of patients' prognostic survival time for better man...

Decoding the role of polyamine metabolism in lung adenocarcinoma prognosis: A triangulated approach combining transcriptome, single-cell and Mendelian randomization analyses.

The progression of lung adenocarcinoma (LUAD) is influenced by polyamine metabolism, which modulates antitumor immunity, although the underlying mecha...

From Records to Relationships: An Ontology-Based Knowledge Graph Framework for Cancer Data Interoperability.

Healthcare data's rapid growth and complexity reveal a significant challenge: we lack effective approaches to integrate multimodal information into un...

Single-cell N4-acetylcytidine regulatory landscape identifies ARIH1 as a ferroptosis-suppressive oncogenic driver in lung adenocarcinoma.

BACKGROUND: N4-acetylcytidine (ac4C) is an emerging post-transcriptional RNA modification implicated in cancer biology, yet its cellular distribution,...

The CT colonography radiology and data system: history, updates, and future directions.

Computed tomography colonography, also known as virtual colonoscopy, is a minimally invasive imaging technique developed in the early 1990s to evaluat...

Large Language Models in Colorectal Cancer Care and Clinical Decision Support: Systematic Review.

BACKGROUND: Colorectal cancer (CRC) is a leading cause of cancer morbidity and mortality worldwide. The complexity of guideline-concordant care and un...

Machine learning and artificial intelligence in liquid biopsy-based early detection of pancreatic cancer: a scoping review.

Pancreatic ductal adenocarcinoma (PDAC) presents as a cancer with an especially poor prognosis, largely due to the challenges surrounding its early di...

LRF-CNN: An explainable lightweight receptive field-based CNN for colorectal cancer histopathological image classification.

Colorectal cancer (CRC) screening and diagnosis rely on histopathological assessment, but many high-performing deep learning (DL) models remain comput...

Preoperative identification of tumor deposits in rectal cancer using a transformer-based multimodal fusion model: a multicenter retrospective study.

OBJECTIVE: To develop and validate a transformer-based deep learning-radiomics model for the non-invasive preoperative discrimination of tumor deposit...

AI-driven volumetric approach for automatic chemotherapy response assessment in colorectal liver metastases.

OBJECTIVES: This study evaluates the clinical utility of an artificial intelligence (AI)-driven volumetric approach for assessing treatment response i...