Colon Cancer

The KMeansGraphMIL Model: A Weakly Supervised Multiple Instance Learning Model for Predicting Colorectal Cancer Tumor Mutational Burden.

Colorectal cancer (CRC) is one of the top three most lethal malignancies worldwide, posing a signifi...

Colorectal cancer classification using weakly annotated whole slide images: Multiple instance learning optimization study.

Colorectal cancer (CRC) is considered one of the most deadly cancer types nowadays. It is rapidly in...

FocusUNet: Pioneering dual attention with gated U-Net for colonoscopic polyp segmentation.

The detection and excision of colorectal polyps, precursors to colorectal cancer (CRC), can improve ...

A novel machine learning-based immune prognostic signature for improving clinical outcomes and guiding therapy in colorectal cancer: an integrated bioinformatics and experimental study.

Immune cells are pivotal components in the tumor microenvironment (TME), which can interact with tum...

SMR-guided molecular subtyping and machine learning model reveals novel prognostic biomarkers and therapeutic targets in non-small cell lung adenocarcinoma.

Non-small cell lung adenocarcinoma (LUAD) is a markedly heterogeneous disease, with its underlying m...

Postoperative fever after elective minimally invasive resection for gastric and colorectal cancer: incidence, risk factors and characteristics.

PURPOSE: To analyze the incidence and risk factors of postoperative fever (POF) in gastrointestinal ...

Multiparametric MRI for Assessment of the Biological Invasiveness and Prognosis of Pancreatic Ductal Adenocarcinoma in the Era of Artificial Intelligence.

Pancreatic ductal adenocarcinoma (PDAC) is the deadliest malignant tumor, with a grim 5-year overall...

CovCysPredictor: Predicting Selective Covalently Modifiable Cysteines Using Protein Structure and Interpretable Machine Learning.

Targeted covalent inhibition is a powerful therapeutic modality in the drug discoverer's toolbox. Re...

Artificial Intelligence Models May Aid in Predicting Lymph Node Metastasis in Patients with T1 Colorectal Cancer.

BACKGROUND/AIMS: Inaccurate prediction of lymph node metastasis (LNM) may lead to unnecessary surger...

The role of endothelial cell-related gene COL1A1 in prostate cancer diagnosis and immunotherapy: insights from machine learning and single-cell analysis.

BACKGROUND: Endothelial cells are integral components of the tumor microenvironment and play a multi...

Integration of single-cell transcriptomics and bulk transcriptomics to explore prognostic and immunotherapeutic characteristics of nucleotide metabolism in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is a highly aggressive tumor with one of the highest morbidit...

Semi-Supervised Detection Model Based on Adaptive Ensemble Learning for Medical Images.

Introducing deep learning technologies into the medical image processing field requires accuracy gua...

Editorial: Modelling esophageal adenocarcinoma.

Comparative study of robotic-assisted vs. laparoscopic surgery for colorectal cancer: a single-center experience.

BACKGROUND: Colorectal cancer (CRC) surgeries are commonly performed using either robotic-assisted c...

Machine learning-based identification of proteomic markers in colorectal cancer using UK Biobank data.

Colorectal cancer is one of the leading causes of cancer-related mortality in the world. Incidence a...

Artificial intelligence-enhanced navigation for nerve recognition and surgical education in laparoscopic colorectal surgery.

BACKGROUND: Devices that help educate young doctors and enable safe, minimally invasive surgery are ...

Deep learning-based prediction of HER2 status and trastuzumab treatment efficacy of gastric adenocarcinoma based on morphological features.

BACKGROUND: First-line treatment for advanced gastric adenocarcinoma (GAC) with human epidermal grow...

Interaction of human gut microbiota and local immune system in progression of colorectal adenoma (MIMICA-1): a protocol for a prospective, observational cohort study.

INTRODUCTION: The current understanding of colorectal carcinogenesis is based on the adenoma-carcino...

A hybrid framework for colorectal cancer detection and U-Net segmentation using polynetDWTCADx.

"PolynetDWTCADx" is a sophisticated hybrid model that was developed to identify and distinguish colo...

Self-interactive learning: Fusion and evolution of multi-scale histomorphology features for molecular traits prediction in computational pathology.

Predicting disease-related molecular traits from histomorphology brings great opportunities for prec...

The combined evaluation of preoperative serum CEA and postoperative tissue CEA as a prognostic factor in stages 0-IV colorectal cancer: a retrospective cohort study.

BACKGROUND: The roles of preoperative serum carcinoembryonic antigen (sCEA) and postoperative tissue...