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Kidney Neoplasms

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Selective Clamping for Robot-Assisted Surgical Procedures.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Partial nephrectomy, the gold standard treatment for renal tumors, is performed with clamping of the renal arteries, in order to interrupt the blood flowing towards the tumor. However, the temporary interruption of arterial flow may lead to ischemia ...

Artificial Intelligence Based Augmented Reality Navigation in Minimally Invasive Partial Nephrectomy.

Urology
OBJECTIVE: To explore the role of artificial intelligence based augmented reality intraoperative real-time navigation in minimally invasive partial nephrectomy to standardize renal hilum dissection procedures and improve operative efficiency.

Machine learning-derived prognostic signature integrating programmed cell death and mitochondrial function in renal clear cell carcinoma: identification of PIF1 as a novel target.

Cancer immunology, immunotherapy : CII
BACKGROUND: The pathogenesis and progression of renal cell carcinoma (RCC) involve complex programmed cell death (PCD) processes. As the powerhouse of the cell, mitochondria can influence cell death mechanisms. However, the prognostic significance of...

Fine-tuned deep learning models for early detection and classification of kidney conditions in CT imaging.

Scientific reports
The kidney plays a vital role in maintaining homeostasis, but lifestyle factors and diseases can lead to kidney failures. Early detection of kidney disease is crucial for effective intervention, often challenging due to unnoticeable symptoms in the i...

Development of an artificial intelligence-generated, explainable treatment recommendation system for urothelial carcinoma and renal cell carcinoma to support multidisciplinary cancer conferences.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Decisions on the best available treatment in clinical oncology are based on expert opinions in multidisciplinary cancer conferences (MCC). Artificial intelligence (AI) could increase evidence-based treatment by generating additional treat...

Histopathology based AI model predicts anti-angiogenic therapy response in renal cancer clinical trial.

Nature communications
Anti-angiogenic (AA) therapy is a cornerstone of metastatic clear cell renal cell carcinoma (ccRCC) treatment, but not everyone responds, and predictive biomarkers are lacking. CD31, a marker of vasculature, is insufficient, and the Angioscore, an RN...

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
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 ...

Predictive Model of Objective Response to Nivolumab Monotherapy for Advanced Renal Cell Carcinoma by Machine Learning Using Genetic and Clinical Data: The SNiP-RCC Study.

JCO clinical cancer informatics
PURPOSE: Anti-PD-1 antibodies are widely used for cancer treatment, including in advanced renal cell carcinoma (RCC). However, the therapeutic response varies among patients. This study aimed to predict tumor response to nivolumab anti-PD-1 antibody ...

Identifying potential risk genes for clear cell renal cell carcinoma with deep reinforcement learning.

Nature communications
Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of renal cell carcinoma. However, our understanding of ccRCC risk genes remains limited. This gap in knowledge poses challenges to the effective diagnosis and treatment of ccRCC. To a...