Colon Cancer

Synthesized colonoscopy dataset from high-fidelity virtual colon with abnormal simulation.

With the advent of the deep learning-based colonoscopy system, the need for a vast amount of high-quality colonoscopy image datasets for training is crucial. However, the generalization ability of deep learning models is challenged by the limited availability of colonoscopy images due to regulatory restrictions and privacy concerns. In this paper, we propose a method for rendering high-fidelity 3D...

Classification of NSCLC subtypes using lung microbiome from resected tissue based on machine learning methods.

Classification of adenocarcinoma (AC) and squamous cell carcinoma (SCC) poses significant challenges for cytopathologists, often necessitating clinical tests and biopsies that delay treatment initiation. To address this, we developed a machine learning-based approach utilizing resected lung-tissue microbiome of AC and SCC patients for subtype classification. Differentially enriched taxa were ident...

Artificial Intelligence-Powered Human Epidermal Growth Factor Receptor 2 and Tumor Microenvironment Analysis in Human Epidermal Growth Factor Receptor 2-Amplified Metastatic Colorectal Cancer: Exploratory Analysis of Phase II TRIUMPH Trial.

PURPOSE: Human epidermal growth factor receptor 2 (HER2)-targeted therapies have shown promise in treating -amplified metastatic colorectal cancer (mC...

Dynamic spectrum-driven hierarchical learning network for polyp segmentation.

Accurate automatic polyp segmentation in colonoscopy is crucial for the prompt prevention of colorectal cancer. However, the heterogeneous nature of p...

Assessment of different U-Net backbones in segmenting colorectal adenocarcinoma from H&E histopathology.

Adenocarcinoma, the most prevalent type of colorectal cancer, makes up roughly 95 % of all cases and is associated with a notably high mortality rate....

Advancing presurgical non-invasive spread through air spaces prediction in clinical stage IA lung adenocarcinoma using artificial intelligence and CT signatures.

BACKGROUND: To accurately identify spread through air spaces (STAS) in clinical stage IA lung adenocarcinoma, our study developed a non-invasive and i...

The role of mitophagy-related genes in prognosis and immunotherapy of cutaneous melanoma: a comprehensive analysis based on single-cell RNA sequencing and machine learning.

Mitophagy, the selective degradation of mitochondria by autophagy, plays a crucial role in cancer progression and therapy response. This study aims to...

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 significant threat to human health. Recently proposed imm...

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 survival rates by up to 90%. Automated polyp segme...

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 increasing due to many factors, such as unhealthy li...

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 molecular mechanisms and prognosis prediction prese...

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 tumor cells and significantly influence cancer progre...

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 cancer (GIC), discuss the influence of POF on shor...

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 survival rate of about 12%. As its incidence and ...

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. Recent advances in covalent drug discovery, in parti...

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 surgery following endoscopic resection of T1 colorectal ...

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 multifaceted role in tumor immunotherapy. Targeting end...

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 morbidity and mortality rates in the world. Nucleotide met...

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

Introducing deep learning technologies into the medical image processing field requires accuracy guarantee, especially for high-resolution images rela...

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 and mortality are predicted to rise globally during...