Improving the qualifications of doctors on the base of intelligent decision support systems
The development of medical intelligent decision-making support systems (IDSS) provides an opportunity not only for advisory assistance at various stages of the medical and diagnostic process, but also the opportunity to improve the qualifications of doctors when using IDSS. The use of IDSS contribu...
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| Format: | Article |
| Language: | English |
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Igor Sikorsky Kyiv Polytechnic Institute
2025-02-01
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| Series: | Adaptivni Sistemi Avtomatičnogo Upravlinnâ |
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| Online Access: | https://asac.kpi.ua/article/view/323692 |
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| author | О. Стенін В. Пасько О. Лісовиченко В. Солдатов |
| author_facet | О. Стенін В. Пасько О. Лісовиченко В. Солдатов |
| author_sort | О. Стенін |
| collection | DOAJ |
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The development of medical intelligent decision-making support systems (IDSS) provides an opportunity not only for advisory assistance at various stages of the medical and diagnostic process, but also the opportunity to improve the qualifications of doctors when using IDSS. The use of IDSS contributes to the acquisition of additional knowledge by the doctor in the case of an incomplete manifestation of the clinical picture and in complex cases, in particular, in rare diseases. This article proposes the structure and composition of the IDSS of medicinal decisions, for which it is proposed to use a combined approach based on the frame structure of the knowledge model using production rules. The production rules issue an explanation understandable to the doctor, which includes a list of signs, taking into account which the diagnostic hypothesis is formed. As an example, several production rules are given regarding the identification of possible diseases of patients based on the level of general blood analysis indicators. The essence of the mechanism of fuzzy logical derivation is to determine the dependence of the output logistic variable (consequent) on the corresponding input logistic variable (antecedent) taking into account the reliability factor and the knowledge importance factor.
Ref. 13, fig. 2
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| format | Article |
| id | doaj-art-b49f9d475dce4ced8d88575d8ae15dcb |
| institution | DOAJ |
| issn | 1560-8956 2522-9575 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Igor Sikorsky Kyiv Polytechnic Institute |
| record_format | Article |
| series | Adaptivni Sistemi Avtomatičnogo Upravlinnâ |
| spelling | doaj-art-b49f9d475dce4ced8d88575d8ae15dcb2025-08-20T03:17:15ZengIgor Sikorsky Kyiv Polytechnic InstituteAdaptivni Sistemi Avtomatičnogo Upravlinnâ1560-89562522-95752025-02-0114610.20535/1560-8956.46.2025.323692362467Improving the qualifications of doctors on the base of intelligent decision support systemsО. Стенін0В. Пасько1О. Лісовиченко2В. Солдатов3Igor Sikorsky Kyiv Polytechnic InstituteIgor Sikorsky Kyiv Polytechnic InstituteIgor Sikorsky Kyiv Polytechnic InstituteIgor Sikorsky Kyiv Polytechnic Institute The development of medical intelligent decision-making support systems (IDSS) provides an opportunity not only for advisory assistance at various stages of the medical and diagnostic process, but also the opportunity to improve the qualifications of doctors when using IDSS. The use of IDSS contributes to the acquisition of additional knowledge by the doctor in the case of an incomplete manifestation of the clinical picture and in complex cases, in particular, in rare diseases. This article proposes the structure and composition of the IDSS of medicinal decisions, for which it is proposed to use a combined approach based on the frame structure of the knowledge model using production rules. The production rules issue an explanation understandable to the doctor, which includes a list of signs, taking into account which the diagnostic hypothesis is formed. As an example, several production rules are given regarding the identification of possible diseases of patients based on the level of general blood analysis indicators. The essence of the mechanism of fuzzy logical derivation is to determine the dependence of the output logistic variable (consequent) on the corresponding input logistic variable (antecedent) taking into account the reliability factor and the knowledge importance factor. Ref. 13, fig. 2 https://asac.kpi.ua/article/view/323692decision makingintelligent systemmedical diagnosisproduction rulesknowledge modelframe structure |
| spellingShingle | О. Стенін В. Пасько О. Лісовиченко В. Солдатов Improving the qualifications of doctors on the base of intelligent decision support systems Adaptivni Sistemi Avtomatičnogo Upravlinnâ decision making intelligent system medical diagnosis production rules knowledge model frame structure |
| title | Improving the qualifications of doctors on the base of intelligent decision support systems |
| title_full | Improving the qualifications of doctors on the base of intelligent decision support systems |
| title_fullStr | Improving the qualifications of doctors on the base of intelligent decision support systems |
| title_full_unstemmed | Improving the qualifications of doctors on the base of intelligent decision support systems |
| title_short | Improving the qualifications of doctors on the base of intelligent decision support systems |
| title_sort | improving the qualifications of doctors on the base of intelligent decision support systems |
| topic | decision making intelligent system medical diagnosis production rules knowledge model frame structure |
| url | https://asac.kpi.ua/article/view/323692 |
| work_keys_str_mv | AT ostenín improvingthequalificationsofdoctorsonthebaseofintelligentdecisionsupportsystems AT vpasʹko improvingthequalificationsofdoctorsonthebaseofintelligentdecisionsupportsystems AT olísovičenko improvingthequalificationsofdoctorsonthebaseofintelligentdecisionsupportsystems AT vsoldatov improvingthequalificationsofdoctorsonthebaseofintelligentdecisionsupportsystems |