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Kidney Neoplasms

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STC-UNet: renal tumor segmentation based on enhanced feature extraction at different network levels.

BMC medical imaging
Renal tumors are one of the common diseases of urology, and precise segmentation of these tumors plays a crucial role in aiding physicians to improve diagnostic accuracy and treatment effectiveness. Nevertheless, inherent challenges associated with r...

The Current Application and Future Potential of Artificial Intelligence in Renal Cancer.

Urology
Artificial intelligence (AI) is the integration of human tasks into machine processes. The role of AI in kidney cancer evaluation, management, and outcome predictions are constantly evolving. We performed a narrative review utilizing PubMed electroni...

Deciphering the tumour microenvironment of clear cell renal cell carcinoma: Prognostic insights from programmed death genes using machine learning.

Journal of cellular and molecular medicine
Clear cell renal cell carcinoma (ccRCC), a prevalent kidney cancer form characterised by its invasiveness and heterogeneity, presents challenges in late-stage prognosis and treatment outcomes. Programmed cell death mechanisms, crucial in eliminating ...

Deep learning-based diagnosis and survival prediction of patients with renal cell carcinoma from primary whole slide images.

Pathology
There is an urgent clinical demand to explore novel diagnostic and prognostic biomarkers for renal cell carcinoma (RCC). We proposed deep learning-based artificial intelligence strategies. The study included 1752 whole slide images from multiple cent...

Predicting tumor mutation burden and VHL mutation from renal cancer pathology slides with self-supervised deep learning.

Cancer medicine
BACKGROUND: Tumor mutation burden (TMB) and VHL mutation play a crucial role in the management of patients with clear cell renal cell carcinoma (ccRCC), such as guiding adjuvant chemotherapy and improving clinical outcomes. However, the time-consumin...

Machine Learning-Enabled Fuhrman Grade in Clear-cell Renal Carcinoma Prediction Using Two-dimensional Ultrasound Images.

Ultrasound in medicine & biology
OBJECTIVE: Accurate assessment of Fuhrman grade is crucial for optimal clinical management and personalized treatment strategies in patients with clear cell renal cell carcinoma (CCRCC). In this study, we developed a predictive model using ultrasound...

Predicting postoperative prognosis in clear cell renal cell carcinoma using a multiphase CT-based deep learning model.

Abdominal radiology (New York)
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...

RCC-Supporter: supporting renal cell carcinoma treatment decision-making using machine learning.

BMC medical informatics and decision making
BACKGROUND: The population diagnosed with renal cell carcinoma, especially in Asia, represents 36.6% of global cases, with the incidence rate of renal cell carcinoma in Korea steadily increasing annually. However, treatment options for renal cell car...