Effective decision support systems in clinical practice and prevention: literature review
Clinical decision support systems (CDSS) often outperform human capabilities for processing a large amount of information, dramatically simplifying the work of specialists and avoiding medical errors. The implementation of such systems is a complex task that requires high-tech developments. The annu...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Concilium Medicum
2023-11-01
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| Series: | КардиоСоматика |
| Subjects: | |
| Online Access: | https://cardiosomatics.ru/2221-7185/article/viewFile/569263/pdf |
| _version_ | 1797606454555836416 |
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| author | Artem A. Komkov Svetlana V. Ryazanova Vladimir P. Mazaev |
| author_facet | Artem A. Komkov Svetlana V. Ryazanova Vladimir P. Mazaev |
| author_sort | Artem A. Komkov |
| collection | DOAJ |
| description | Clinical decision support systems (CDSS) often outperform human capabilities for processing a large amount of information, dramatically simplifying the work of specialists and avoiding medical errors. The implementation of such systems is a complex task that requires high-tech developments. The annual increase in the development of such systems has a geometric progression. However, it is unclear if most of them will be integrated into clinical practice and recommendations. The use of CDSS to address various disease diagnosis, treatment, and prevention issues is demonstrated, and possible linkages between scientific clinical observations and CDSS are examined. Currently, many data gathering and processing systems use machine learning algorithms and convolutional technologies to create CDSS, resulting in data that exceeds the ability of human thinking to determine the logic of recommended decisions. This study presents the most studied modern CDSS, the possibilities of their application, and the implementation issues. |
| first_indexed | 2024-03-11T05:15:25Z |
| format | Article |
| id | doaj.art-cc1cc6afb3e04b9a8d0146317a4b7953 |
| institution | Directory Open Access Journal |
| issn | 2221-7185 2658-5707 |
| language | English |
| last_indexed | 2024-03-11T05:15:25Z |
| publishDate | 2023-11-01 |
| publisher | Concilium Medicum |
| record_format | Article |
| series | КардиоСоматика |
| spelling | doaj.art-cc1cc6afb3e04b9a8d0146317a4b79532023-11-17T18:16:08ZengConcilium MedicumКардиоСоматика2221-71852658-57072023-11-0114317718510.17816/CS56926376546Effective decision support systems in clinical practice and prevention: literature reviewArtem A. Komkov0https://orcid.org/0000-0001-7159-1790Svetlana V. Ryazanova1https://orcid.org/0000-0001-6776-0694Vladimir P. Mazaev2https://orcid.org/0000-0002-9782-0296National Medical Research Center of Therapy and Preventive MedicineNational Medical Research Center of Therapy and Preventive MedicineNational Medical Research Center of Therapy and Preventive MedicineClinical decision support systems (CDSS) often outperform human capabilities for processing a large amount of information, dramatically simplifying the work of specialists and avoiding medical errors. The implementation of such systems is a complex task that requires high-tech developments. The annual increase in the development of such systems has a geometric progression. However, it is unclear if most of them will be integrated into clinical practice and recommendations. The use of CDSS to address various disease diagnosis, treatment, and prevention issues is demonstrated, and possible linkages between scientific clinical observations and CDSS are examined. Currently, many data gathering and processing systems use machine learning algorithms and convolutional technologies to create CDSS, resulting in data that exceeds the ability of human thinking to determine the logic of recommended decisions. This study presents the most studied modern CDSS, the possibilities of their application, and the implementation issues.https://cardiosomatics.ru/2221-7185/article/viewFile/569263/pdfclinical decision support systemmachine learning |
| spellingShingle | Artem A. Komkov Svetlana V. Ryazanova Vladimir P. Mazaev Effective decision support systems in clinical practice and prevention: literature review КардиоСоматика clinical decision support system machine learning |
| title | Effective decision support systems in clinical practice and prevention: literature review |
| title_full | Effective decision support systems in clinical practice and prevention: literature review |
| title_fullStr | Effective decision support systems in clinical practice and prevention: literature review |
| title_full_unstemmed | Effective decision support systems in clinical practice and prevention: literature review |
| title_short | Effective decision support systems in clinical practice and prevention: literature review |
| title_sort | effective decision support systems in clinical practice and prevention literature review |
| topic | clinical decision support system machine learning |
| url | https://cardiosomatics.ru/2221-7185/article/viewFile/569263/pdf |
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