Colon Cancer

Enhancing Surgeons' Cognitive Performance in Colorectal Surgery: A Narrative Review.

BACKGROUND: Colorectal surgery continues to exhibit variability in outcomes despite advancements in minimally invasive and robotic techniques. Increasing evidence suggests that this inconsistency is driven less by technical proficiency than by unstructured, experience-dependent decision-making. OBJECTIVE: This article presents a hybrid narrative review and perspective that examines the cognitive u...

Spectral CT imaging in colorectal cancer: current applications, limitations, and future perspectives.

Colorectal cancer (CRC) is the third most common malignancy worldwide, and early detection is vital to prevent metastasis and postoperative recurrence. This review summarizes current applications of spectral computed tomography (CT) in CRC, including its principles, spectral parameters used for evaluating primary and metastatic lesions, and key findings from recent literature. A systematic search ...

Clinical Impact of Artificial Intelligence-Augmented Lymph Node Evaluation in Metastatic Gastric, Colorectal, and Breast Cancer.

CONTEXT.—: Lymph node (LN) assessment plays a critical role in cancer staging and prognosis but remains a time-consuming and labor-intensive task in p...

Integrative single-cell and machine learning framework reveals prognostic fibroblast subtypes and constructs a fibroblast-related risk signature in lung adenocarcinoma.

Machine learning-driven computational drug repurposing to identify new tubulin inhibitors against cancer.

Tubulin is a validated anticancer target, yet the clinical translation of colchicine-binding site inhibitors remains limited by toxicity and resistanc...

Spatial and multi-omics transcriptomic dissects platinum resistance in lung adenocarcinoma: a five-gene predictive model with tumor microenvironment dynamics.

The scarcity of reliable biomarkers and predictive models for platinum resistance in lung adenocarcinoma (LUAD) poses a significant clinical challenge...

AI-driven biomarker learning for the early diagnosis of neurodegenerative diseases: ABLEDx.

BACKGROUND: Tears are an easily accessible biofluid that reflects both emotional states and disease conditions. They are particularly enriched in extr...

Synergistic DBNDD1-GDF15 Signaling Activates the NF-κB Pathway to Promote Colorectal Cancer Progression.

UNLABELLED: Colorectal cancer is a highly lethal gastrointestinal tract malignancy whose pathogenesis and molecular drivers are not fully understood. ...

Extracellular vesicles in colorectal cancer: immunomodulation, diagnostics, and therapeutic perspectives.

Colorectal cancer (CRC) remains a significant global health concern and is among the leading causes of cancer-related mortality. The disease often pro...

Controversies in Computer-Assisted Detection in Colonoscopy.

BACKGROUND: Artificial intelligence (AI) applications in endoscopy, particularly computer-aided detection (CADe), have shown consistent benefit in ran...

AI-enhanced robotic hands: a breakthrough in early tumour detection and removal.

AI-enhanced robotic hands are rapidly reshaping tumour surgery by merging real-time sensing, precision mechanics, and intelligent decision support, ye...

Effectiveness of AI-enhanced colonoscopy: A case-control study using real world evidence in a young screening age population.

BACKGROUND: Computer aided detection (CADe) colonoscopy has been shown in randomized controlled trials to improve detection of adenomatous colorectal ...

Rapid, label-free cancer detection in fresh pancreatic tissue using deep learning and multispectral Mueller matrix polarimetry.

BACKGROUND: Frozen section (FS) tissue assessment is essential for guiding intraoperative surgical decision-making in oncology, particularly in proced...

Comparison of artificial intelligence and multidisciplinary team recommendations in the management of colorectal cancer liver metastases.

Multidisciplinary teams (MDTs) are central to treatment planning for colorectal cancer liver metastases (CRCLM) but require time and consistent access...

Generalisation of automatic tumour segmentation in histopathological whole-slide images across multiple cancer types.

Deep learning is expected to aid pathologists in tasks such as tumour segmentation. We developed a general tumour segmentation model for histopatholog...

TabPFN-driven ternary classification of stage IA lung adenocarcinoma subtypes using AI-derived histogram features a retrospective multicenter cohort study.

BACKGROUND: Preoperative differentiation of precursor glandular lesions (PGL), minimally invasive (MIA), and invasive adenocarcinoma (IAC) in stage IA...

Machine learning framework for mRNA alternative splicing analysis identifies a signature of progression in colorectal adenocarcinoma.

Despite recent advances in genome-wide profiling and the discovery of novel therapeutic options for colorectal adenocarcinoma (COAD), effective patien...

Interpretable machine learning based decision-making system for lung adenocarcinoma metastasis: a population-based study with exploration of multi-classification models.

A knowledge-driven self-supervised learning method for enhancing EEG-based emotion recognition.

Emotion recognition brain-computer interface (BCI) using electroencephalography (EEG) is crucial for human-computer interaction, medicine, and neurosc...

IR Spectroscopy and Linear Support Vector Machine Analysis of Colorectal Liver Metastasis.

The Colorectal Liver Metastasis (CLM) library contains 756,096 full range Fourier transform infrared (FTIR) microscope imaging spectra of 14 frozen ti...