ETHNOPHARMACOLOGICAL RELEVANCE: Mulberry leaves have been used as traditional hypoglycemic medicine-food plant for thousand years in China. According to traditional Chinese medicine theory, type 2 diabetes mellitus (T2DM) belongs to the category of X...
RESEARCH QUESTION: What is the intra- and inter-centre reliability in embryo grading performed according to the Istanbul Consensus across several IVF clinics?
BACKGROUND: LDL-C is a strong risk factor for cardiovascular disorders. The formulas used to calculate LDL-C showed varying performance in different populations. Machine learning models can study complex interactions between the variables and can be ...
International journal of molecular sciences
Oct 6, 2021
In silico approaches have been studied intensively to assess the toxicological risk of various chemical compounds as alternatives to traditional in vivo animal tests. Among these approaches, quantitative structure-activity relationship (QSAR) analysi...
Medical images are difficult to comprehend for a person without expertise. The scarcity of medical practitioners across the globe often face the issue of physical and mental fatigue due to the high number of cases, inducing human errors during the di...
Feature selection (marker gene selection) is widely believed to improve clustering accuracy, and is thus a key component of single cell clustering pipelines. Existing feature selection methods perform inconsistently across datasets, occasionally even...
IEEE journal of biomedical and health informatics
Oct 6, 2021
Keratoconus is one of the most severe corneal diseases, which is difficult to detect at the early stage (i.e., sub-clinical keratoconus) and possibly results in vision loss. In this paper, we propose a novel end-to-end deep learning approach, called ...
Ureteropelvic junction obstruction (UPJO) is one of the common causes of hydronephrosis in children, and the purpose of this study was to observe the application effect of da Vinci robot-assisted laparoscopic treatment of UPJO and to investigate the ...
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