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Gene Expression Regulation, Neoplastic

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Prognostic value of CDKN2A in head and neck squamous cell carcinoma via pathomics and machine learning.

Journal of cellular and molecular medicine
This study aims to enhance the prognosis prediction of Head and Neck Squamous Cell Carcinoma (HNSCC) by employing artificial intelligence (AI) to analyse CDKN2A gene expression from pathology images, directly correlating with patient outcomes. Our ap...

Machine Learning-Based Pathomics Model to Predict the Prognosis in Clear Cell Renal Cell Carcinoma.

Technology in cancer research & treatment
Clear cell renal cell carcinoma (ccRCC) is a highly lethal urinary malignancy with poor overall survival (OS) rates. Integrating computer vision and machine learning in pathomics analysis offers potential for enhancing classification, prognosis, and ...

Molecular characterization, immunocorrelation analysis, WGCNA analysis and machine learning modeling of genes associated with copper death subtypes of laryngeal cancer.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Laryngeal cancer is a malignant tumor that originates from the mucous membrane of the larynx. Currently, the specific involvement mechanism of copper death in laryngeal cancer patients has not been deeply studied.

Insights into a Machine Learning-Based Palmitoylation-Related Gene Model for Predicting the Prognosis and Treatment Response of Breast Cancer Patients.

Technology in cancer research & treatment
BACKGROUND: Breast cancer is a prevalent public health concern affecting numerous women globally and is associated with palmitoylation, a post-translational protein modification. Despite increasing focus on palmitoylation, its specific implications f...

Machine Learning Identify Ferroptosis-Related Genes as Potential Diagnostic Biomarkers for Gastric Intestinal Metaplasia.

Technology in cancer research & treatment
BACKGROUND: Gastric intestinal metaplasia(GIM) is an independent risk factor for GC, however, its pathogenesis is still unclear. Ferroptosis is a new type of programmed cell death, which may be involved in the process of GIM. The purpose of this stud...

Patterns of Gene Expression Profiles Associated with Colorectal Cancer in Colorectal Mucosa by Using Machine Learning Methods.

Combinatorial chemistry & high throughput screening
BACKGROUND: Colorectal cancer (CRC) has a very high incidence and lethality rate and is one of the most dangerous cancer types. Timely diagnosis can effectively reduce the incidence of colorectal cancer. Changes in para-cancerous tissues may serve as...

Machine learning on thyroid disease: a review.

Frontiers in bioscience (Landmark edition)
This study reviews the recent progress of machine learning for the early diagnosis of thyroid disease. Based on the results of this review, different machine learning methods would be appropriate for different types of data for the early diagnosis of...

Detection of subtype-specific breast cancer surface protein biomarkers via a novel transcriptomics approach.

Bioscience reports
BACKGROUND: Cell-surface proteins have been widely used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. So far, very few attempts have been made to characterize the surfaceome of patien...

An artificial neural network model based on DNA damage response genes to predict outcomes of lower-grade glioma patients.

Briefings in bioinformatics
Although the prognosis of lower-grade glioma (LGG) patients is better than others, outcomes are highly heterogeneous. Isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status can identify patient subsets with different prognosis. However,...