Algorithm of diagnostics of medical datas based on symptom complexes

Akhram H. Nishanov; Gulomjon P. Djuraevb; Malika A. Khasanova; Saidqul X. Saparov; Fazilbek M. Zaripov

doi:10.1117/12.2669449

5 January 2023 Algorithm of diagnostics of medical datas based on symptom complexes

Akhram H. Nishanov, Gulomjon P. Djuraevb, Malika A. Khasanova, Saidqul X. Saparov, Fazilbek M. Zaripov

Proceedings Volume 12564, 2nd International Conference on Computer Applications for Management and Sustainable Development of Production and Industry (CMSD-II-2022); 125640W (2023) https://doi.org/10.1117/12.2669449
Event: Computer Applications for Management and Sustainable Development of Production and Industry (CMSD2022), 2022, Dushanbe, Tajikistan

Abstract

In the clinical practice of medical diagnostics, special attention is paid to the problems of the formation of symptom complexes that classify diagnostic objects by world researchers as a result of an increase in the number of symptoms that correctly identify diseases. As a rule, this research was limited to the transition from the entire proposed group of symptoms to a small group of symptoms, that is, the selection of a significant group of symptoms, the size of which was small, based on a rule of law or criterion. And this group of symptoms is called symptom complexes. According to recent studies by scientists from all over the world, the total sum of the totality of selected symptom complexes in relation to the number given as symptom complexes is understood as the result of an increase in the number of symptoms included in this group compared to the previously indicated quantitative indicators. Here, the research is carried out in two stages: initially, a set of all symptom complexes is determined in relation to the required number, then the total amount of the complexes is obtained. These suggested actions will be related to the development of strictly based mathematical methods and algorithms, theoretical research and algorithmic and software for solving practical problems. The article analyzes the diagnosis (classification) of medical logotypes based on informative symptomatic complexes (see Table 2) selected for ischemic heart dis-eases (5 classes, so class X1-,“Stenocardia tension”, class X2-“Acute myo-cardial infarction”, class X3 -“Arrhythmic form”, class X4-“Postinfarction cardiosclerosis”, class X5- “Permanent form of atrial fibrillation”) obtained as an object of study, based on the proposed algorithm.

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Akhram H. Nishanov, Gulomjon P. Djuraevb, Malika A. Khasanova, Saidqul X. Saparov, and Fazilbek M. Zaripov "Algorithm of diagnostics of medical datas based on symptom complexes", Proc. SPIE 12564, 2nd International Conference on Computer Applications for Management and Sustainable Development of Production and Industry (CMSD-II-2022), 125640W (5 January 2023); https://doi.org/10.1117/12.2669449

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KEYWORDS

Algorithm development

Heart

Cardiovascular disorders

Diseases and disorders

Matrices

Diagnostics

Blood

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