Artificial intelligence is increasingly being used to improve diagnosis and prognostication for acute and chronic kidney diseases. Studies published in 2019 relied on a variety of available data sources towards this objective, including electronic he...
The aim of our study is to evaluate the mechanisms of anti-inflammatory property of Tagetes patula L. (French Marigold) flower extracts and its protective effect on renal epithelium against uropathogenic E. coli infection. Thus, in this study, a numb...
In this research, we exploit an image-based deep learning framework to distinguish three major subtypes of renal cell carcinoma (clear cell, papillary, and chromophobe) using images acquired with computed tomography (CT). A biopsy-proven benchmarking...
AIM: Analysis of etiology, clinical and morphological manifestations, approaches to therapy and prognosis of membranoproliferative glomerulonephritis (MPGN).
CONTEXT: Tsothel, a traditional Tibetan medicine, is regarded as 'the king of essences'. Nevertheless, tsothel has aroused serious concern regarding its biosafety because its main component is HgS. Unfortunately, toxicological studies on tsothel are ...
We investigate the viability of statistical relational machine learning algorithms for the task of identifying malignancy of renal masses using radiomics-based imaging features. Features characterizing the texture, signal intensity, and other relevan...