View clinical trials related to Radiomics.
Filter by:The aim of this study was to develop an radiomic model based on CT images to evaluate markers of the bladder cancer microenvironment, such as TSR,TIL, and IP. Secondly, the association of the radiomic model with clinical outcomes and immunotherapy response was investigated.
Renal cell carcinoma (RCC) is the most common malignant tumor in the kidney with a high mortality rate. Traditional imaging techniques are limited in capturing the internal heterogeneity of the tumor. Radiomics provides internal features of lesions for precise diagnosis, prognosis prediction, and personalized treatment planning. Early and accurate diagnosis of renal tumors is crucial, but it's challenging due to morphological and pathological overlap between benign and malignant lesions. The accurate diagnosis of RCC, especially for small tumors, remains a significant challenge. Recent studies have shown a relationship between body composition, obesity, and renal tumors. Common indicators like body weight and BMI fail to reflect body composition accurately. Research on the role of body composition, including adipose tissue, in tumor pathology could improve clinical diagnosis and treatment planning.
The purpose of this study is to compare AI performance to doctor's performance in the evaluation of IPF/UIP and ILDs without UIP(proven by biopsy).
A test-retest study on the stability and repeatability of healthy skin features on OCT