BACKGROUND AND OBJECTIVES: A lot of research has been directed towards medicinal plants which are considered as a source of multiple phytotherapic substances endowed with hypoglycemic activities that could be used to treat diabetes and its complicati...
BACKGROUND: This study evaluates the effects of training (on running distance measured with a Cooper test) in 3 weeks in non-professional athletes using PycnoRacer®, a fitness drink (FD) including Pycnogenol® during the training period.
OBJECTIVE: This study evaluated the characteristics of new users of sodium glucose co-transporter 2 inhibitors (SGLT2i) in clinical practice to assess the applicability of the findings from clinical trials (Empagliflozin, Cardiovascular Outcomes and ...
OBJECTIVE: To investigate whether endogenous nociceptin/orphanin FQ (N/OFQ) can inhibit arrhythmia and expression of β-adrenergic receptor (β-AR) on the surface of myocardial cell membrane in acute myocardial ischemia rats by Raf kinase inhibitory pr...
Network physiology describes the human body as a complex network of interacting organ systems. It has been applied successfully to determine topological changes in different sleep stages. However, the number of network links can quickly grow above th...
Clinical and translational gastroenterology
Dec 1, 2019
OBJECTIVES: Application of artificial intelligence in gastrointestinal endoscopy is increasing. The aim of the study was to examine the accuracy of convolutional neural network (CNN) using endoscopic images for evaluating Helicobacter pylori (H. pylo...
Zhonghua wai ke za zhi [Chinese journal of surgery]
Dec 1, 2019
To examine the value and clinical application of convolutional neural network in pathological diagnosis of metastatic lymph nodes of gastric cancer. Totally 124 patients with advanced gastric cancer who underwent radical gastrectomy plus D2 lymphad...
Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies
Dec 1, 2019
OBJECTIVES: To deploy machine learning tools (random forests) to develop a model that reliably predicts hospital mortality in children with acute infections residing in low- and middle-income countries, using age and other variables collected at hosp...
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