Technology in cancer research & treatment
39703069
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 ...
BACKGROUND: Chronic Kidney Disease (CKD) is a common severe complication after radical nephrectomy in patients with renal cancer. The timely and accurate prediction of the long-term progression of renal function post-surgery is crucial for early inte...
BACKGROUND: Centrosome amplification (CA) has been shown to be capable of initiating tumorigenesis with metastatic potential and enhancing cell invasion. We were interested in discovering how centrosome amplification-associated signature affects the ...
OBJECTIVE: To investigate the value of multiparametric magnetic resonance imaging (MRI) as a non-invasive method to predict the aggressiveness of renal cell carcinoma (RCC) by developing a convolutional neural network (CNN) model and fusing it with c...
RATIONALE AND OBJECTIVES: The management of complex renal cysts is guided by the Bosniak classification system, which may be inadequate for risk stratification of patients to determine the appropriate intervention. Radiomics models based on CT imagin...
The connection between metabolic reprogramming and tumor progression has been demonstrated in an increasing number of researches. However, further research is required to identify how metabolic reprogramming affects interpatient heterogeneity and pro...
Recently, as the number of cancer patients has increased, much research is being conducted for efficient treatment, including the use of artificial intelligence in genitourinary pathology. Recent research has focused largely on the classification of ...
PURPOSE: To create a computer-aided prediction (CAP) system to predict Wilms tumor (WT) responsiveness to preoperative chemotherapy (PC) using pre-therapy contrast-enhanced computed tomography (CECT).