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...

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Bibliographic Details
Main Authors: Artem A. Komkov, Svetlana V. Ryazanova, Vladimir P. Mazaev
Format: Article
Language:English
Published: Concilium Medicum 2023-11-01
Series:КардиоСоматика
Subjects:
Online Access:https://cardiosomatics.ru/2221-7185/article/viewFile/569263/pdf
Description
Summary: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.
ISSN:2221-7185
2658-5707