About the author: |
S. K. Kulishov, I. M. Skrypnyk, G. S. Maslova, O. A. Shaposhnyk, I. P. Kudria, N. P. Prykhodko, T. I. Shevchenko |
Heading |
CLINICAL MEDICINE |
Type of article |
Scentific article |
Annotation |
The purpose of the study was optimizing the diagnosis of the inflammatory syndrome with an autoimmune component in patients with acute myocardial infarction using a quantum genetic algorithm and graph neural networks. There were 47 patients observed with acute myocardial infarction, and among them, 35 experienced complications. The diagnostic criteria of the inflammatory syndrome with an autoimmune component include elevated level of ratio of chaperone 60 autoantibodies to interleukin-10 more than 4.99 conditional units, ratio of chaperone 60 autoantibodies to C-reactive protein more than 4.2 conventional units, ratio of C-reactive protein to interleukin-10 is less than 0.2 conventional units. This syndrome was present in 33 (70.2 %) out of 47 myocardial infarction patients (p=0.01 by the Chi-Square test). It was presented on visual programming language “Dragon”. Quantum genetic algorithm, graph neural networks using for making decisions for an inflammation syndrome with autoimmune component diagnosis presented in this investigation. |
Tags |
Graph neural networks,inflammation syndrome with autoimmune component,acute myocardial infarction,diagnosis |
Bibliography |
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Publication of the article |
«World of Medicine and Biology» №1(87), 2024 year, 090-094 pages, index UDK 616.127-005.8-085 |
DOI |
10.26724/2079-8334-2024-1-87-90-94 |