Bratisl Med J
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The aim of this study is to describe the colorectal cancer trend in the Slovakia between 2002 and 2019. ⋯ The situation of colorectal cancer trend in the Slovakia has improved compared to the previous period (1971-2001) (Tab. 4, Fig. 4, Ref. 34).
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LETTER TO EDITOR Keywords.
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Insulin resistance (IR) is a consequence of chronic adipose tissue inflammation and underlies the pathogenesis of several diseases, such as type 2 diabetes mellitus, cardiovascular diseases and metabolic syndrome. In this study, we examined the association between dyslipidaemia and IR; directly comparing conventional lipid ratios and apoB/apoA1 ratios for strength and independence as risk factors for IR in a Kazakh population. ⋯ In our study, IR was more common in Kazakh women than in Kazakh men. IR was also associated with apoB and TG levels. Thus, we suggest that analysis of TG, apoB and apoB/apoA1 ratio may be recommended as early predictors of IR risk in the Kazakh population (Tab. 3, Ref. 22). Text in PDF www.elis.sk Keywords: insulin resistance, dyslipidaemia, apolipoproteins, triglycerides, lipids.
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The relationship between epicardial adipose tissue and inflammatory events has been shown in many studies. Because it is an inflammatory process in coronary progression, it is aimed to examine the relationship between coronary artery disease progression and epicardial adipose tissue thickness. ⋯ An independent relationship was found between epicardial adipose tissue and coronary artery progression. In the light of these findings, it can be concluded that epicardial adipose tissue residue is effective in the development of coronary artery stenosis and calcific-atherosclerotic changes in the coronary arteries. In the light of the information obtained, a positive correlation was determined between epicardial adipose tissue thickness and coronary artery disease (Tab. 3, Fig. 2, Ref. 15). Text in PDF www.elis.sk Keywords: coronary artery disease, epicardial adipose tissue, progression.
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The neuro developmental condition known as Autism Spectrum Disorder (ASD) affects people on a lifetime basis and exhibits itself in a wide range of ways. In this research work a brand-new semi-supervised training method for the recognition of discrete multi-modal autism spectrum disorder is proposed. At the coarse-grained level, we consider that various methodologies are anticipated to explore equivalent information about child autism. ⋯ Deep Coupled AlexNet is developed to obtain 98.13 % of accuracy, 95.1 % of precision, 94.3 % of recall and 95.4 of F1-score for OMEGE dataset. Moreover, 98.6 % of accuracy, 97.2 % of precision, 98.5 of recall and 97.5 % of F1-score for DIAEMO dataset (Tab. 8, Fig. 10, Ref. 16). Keywords: autism spectrum disorder, artificial neural networks, emotion recognition, interaction design, multimodal factors.