AIMC Topic: Kidney Neoplasms
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A Spatial Metabolomics Annotation Workflow Leveraging Cyclic Ion Mobility and Machine Learning-Predicted Collision Cross Sections.
Journal of the American Society for Mass Spectrometry
Jun 4, 2025
In nontargeted spatial metabolomics, accurate annotation is crucial for understanding metabolites' biological roles and spatial patterns. MS mass spectrometry imaging (MSI) coverage is often incomplete or nonexistent, resulting in many unknown featur...
From planning to prognosis: predicting renal function after minimally-invasive partial nephrectomy with artificial intelligence.
Minerva urology and nephrology
Jun 1, 2025
This study presents a machine learning model to predict renal function decline following minimally-invasive partial nephrectomy. Using a dataset of 556 patients treated between 2015 and 2023, the model incorporated patient, tumor, and intraoperative ...
Integrative PPI network and random forest analysis identifies KIF4A, TOP2A, and ASPM protein macromolecules as novel protein biomarkers in renal carcinoma pathogenesis.
International journal of biological macromolecules
Jun 1, 2025
The pathogenesis of kidney cancer is not fully understood, so there is an urgent need to identify new biomarkers to improve diagnosis and treatment. The study identified KIF4A, TOP2A and ASPM as novel protein biomarkers for renal cancer and explored ...
Poly-ADP-Ribose Binding Proteins
DNA Topoisomerases, Type II
Gene Expression Regulation, Neoplastic
Nerve Tissue Proteins
Epithelial-Mesenchymal Transition
Gene Expression Profiling
Humans
Random Forest
Cell Line, Tumor
Prognosis
Kidney Neoplasms
Protein Interaction Maps
Biomarkers, Tumor
Carcinoma, Renal Cell
Computational Biology
Kinesins
Integrated machine learning survival framework develops a prognostic model based on macrophage-related genes and programmed cell death signatures in a multi-sample Kidney renal clear cell carcinoma.
Cell biology and toxicology
May 30, 2025
BACKGROUND: Macrophages are closely associated with the progression of Kidney renal clear cell carcinoma (KIRC) and can influence programmed cell death (PCD) of tumour cells. To identify prognostic biomarkers for KIRC, it is essential to investigate ...
Integrating machine learning and multi-omics analysis to unveil key programmed cell death patterns and immunotherapy targets in kidney renal clear cell carcinoma.
Scientific reports
May 26, 2025
Kidney renal clear cell carcinoma (KIRC), a cancer characterized by substantial immune infiltration, exhibits limited sensitivity to conventional radiochemotherapy. Although immunotherapy has shown efficacy in some patients, its applicability is not ...
Application of BOLDMRIbased radiomics in differentiating malignant from benign renal tumors.
Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences
May 13, 2025
OBJECTIVES: Blood oxygen level dependent magnetic resonance imaging (BOLD-MRI) is a kind of non-invasive MRI technology which reflects the tissue blood oxyen levels. This stuy aims to explore the value of radiomics based on BOLD-MRI in differentiatin...
[ARTIFICIAL INTELLIGENCE-ASSISTED LITERATURE REVIEW: A CASE STUDY IN FUMARATE HYDRATASE-DEFICIENT RENAL CELL CARCINOMA].
Harefuah
May 1, 2025
Fumarate hydratase-deficient renal cell carcinoma (FHdRCC) is a rare and aggressive form of kidney cancer that presents significant therapeutic challenges. Due to its rarity, treatment decisions often rely on comprehensive literature reviews to ident...
[Usage of artificial intelligence in the clinical practice of urologists in observations with renal parenchymal neoplasms].
Urologiia (Moscow, Russia : 1999)
May 1, 2025
OBJECTIVE: to assess the needs and attitudes of urologists regarding the use of technologies related to artificial intelligence, particularly the web platform "Sechenov.AI_nephro", in the surgical treatment of patients with renal parenchymal neoplasm...
Predicting postoperative prognosis in clear cell renal cell carcinoma using a multiphase CT-based deep learning model.
Abdominal radiology (New York)
May 1, 2025
BACKGROUND: Some clinicopathological risk stratification systems (CRSSs) such as the leibovich score have been used to predict the postoperative prognosis of patients with clear cell renal cell carcinoma (ccRCC), but there are no reliable noninvasive...
Integrating Bioinformatics and Machine Learning to Identify Glucose Metabolism-Related Biomarkers with Diagnostic and Prognostic Value for Patients with Kidney Renal Clear Cell Carcinoma.
Archivos espanoles de urologia
Apr 1, 2025
BACKGROUND: Glucose metabolism plays a critical role in the development and progression of kidney renal clear cell carcinoma (KIRC). This study aimed to identify glucose metabolism-related biomarkers (GRBs) and therapeutic targets for KIRC diagnosis ...
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