Analysis of the structure of the medical decision support rules system based on the dependency graph

Ruslan Vafin, Rashit Nasyrov, Rustem Zulkarneev

Abstract


Currently, one of the promising areas in medicine is personalized medicine, which allows selecting the optimal treatment for each individual patient. Within the framework of the national program "Digital Economy of the Russian Federation", artificial intelligence technologies are the most promising for solving the problems of personalized medicine. The most important areas of application of artificial intelligence is the analysis of a large volume of medical texts, for example, electronic medical records or various professional medical literature, as well as image recognition of various formats. Currently, a large amount of medical knowledge about various diseases has been accumulated, formalized in the form of clinical guidelines (CG). For general practitioners, the need to regularly master a large volume of textual medical information leads to information overload, and, accordingly, a decrease in the effectiveness of the processes of diagnosis, treatment and rehabilitation of patients. The main direction for solving this problem is the use of clinical decision support systems (CDSS), which are based on the decision-making rules formulated on the basis of the CG. This article discusses an analysis of a structure of relationship in decision rules system for CDSS, implemented in the logic programming language Prolog.

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References


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