AIMC Topic: Kidney Neoplasms

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Construction and multi-omics analysis of ccRCC mitochondrial related gene machine learning model and validate of key gene FKBP10.

International immunopharmacology
BACKGROUND: Clear cell renal cell carcinoma represents the most prevalent histological subtype of renal malignancy Emerging evidence underscores the critical involvement of mitochondrial dysfunction in oncogenesis and tumor progression. In this study...

KPNA2 expression as a biomarker for immunosuppressive microenvironment predicting response to TKI and immunotherapy in metastatic renal cell carcinoma.

European journal of pharmacology
BACKGROUND: Immunotherapy (IO) combined with tyrosine kinase inhibitors (TKI) are now first-line therapy for advanced renal cell carcinoma (RCC), though reliable predictive biomarkers remain elusive. Recent evidence demonstrates that karyopherin α2 s...

Utilisation of artificial intelligence to enhance the detection rates of renal cancer on cross-sectional imaging: protocol for a systematic review and meta-analysis.

BMJ open
INTRODUCTION: The incidence of renal cell carcinoma has steadily been on the increase due to the increased use of imaging to identify incidental masses. Although survival has also improved because of early detection, overdiagnosis and overtreatment o...

Machine learning-assisted radiogenomic analysis for miR-15a expression prediction in renal cell carcinoma.

BMC cancer
BACKGROUND: Renal cell carcinoma (RCC) is a prevalent malignancy with highly variable outcomes. MicroRNA-15a (miR-15a) has emerged as a promising prognostic biomarker in RCC, linked to angiogenesis, apoptosis, and proliferation. Radiogenomics integra...

Anoikis-related genes predicts prognosis and therapeutic response in renal cell carcinoma.

Annals of medicine
BACKGROUND: Metastasis represents the primary cause of cancer-related mortality, with a high incidence observed in renal cell carcinoma (RCC). Anoikis, a specialized form of apoptosis, plays a crucial role in preventing displaced cells from adhering ...

Optimized machine learning based comparative analysis of predictive models for classification of kidney tumors.

Scientific reports
The kidney is an important organ that helps clean the blood by removing waste, extra fluids, and harmful substances. It also keeps the balance of minerals in the body and helps control blood pressure. But if the kidney gets sick, like from a tumor, i...

Development and evaluation of deep neural networks for the classification of subtypes of renal cell carcinoma from kidney histopathology images.

Scientific reports
Kidney cancer is a leading cause of cancer-related mortality, with renal cell carcinoma (RCC) being the most prevalent form, accounting for 80-85% of all renal tumors. Traditional diagnosis of kidney cancer requires manual examination and analysis of...

A densely connected framework for cancer subtype classification.

BMC bioinformatics
BACKGROUND: Reliable identification of cancer subtypes is crucial for devising personalized treatment strategies. Integrating multi-omics data has proven to be an effective method for analyzing cancer subtypes. By combining molecular information acro...

Use of hybrid quantum-classical algorithms for enhancing biomarker classification.

PloS one
Quantum machine learning (QML) combines quantum computing with machine learning, offering potential for solving intricate problems. Our research delves into QML's application in identifying gene expression biomarkers for clear cell renal cell carcino...

Driven early detection of chronic kidney cancer disease based on machine learning technique.

PloS one
In recent times, chronic kidney cancer has been considered a significant cause of cancer, and Renal Cell Carcinoma (RCC) has become a significant prevalent among various kidney cancer conditions. The analysis of kidney cancer, an important and often ...