Expert system for the study of psychoneuro-logical diseases using the method of differential diagnostics
DOI:
https://doi.org/10.31498/2225-6733.45.2022.276223Keywords:
expert system, decision-making mechanism, frame, knowledge baseAbstract
The article reveals the topic of developing an expert system of psychoneurological diseases using the method of differential diagnostics. The task of the system of differential medical diagnosis is to determine the diseases that the patient may suffer from, based on the observation of his symptoms. The method used in diagnosing the disease is differential. This method weeds out diseases because they do not match any facts or symptoms, which in the end must lead to the only possible disease. The developed and implemented expert system includes: a mechanism for accessing the database of symptoms for each of the correlating diseases, an algorithm for forming ES input parameters, a decision-making method based on a logical mechanism. Various decision-making mechanisms were investigated and analyzed in the work, which made it possible to avoid shortcomings and improve the work of the expert system. ES work relies on a knowledge base of symptoms. The database is a collection of differential diagnostic features, corresponding frequencies of occurrence for each of the diagnosed diseases. The application has two modes of operation: the mode of operation with the knowledge base, which provides direct work with the database and support for all necessary operations for the full functioning of the system. The mode of analysis in which the specialist receives support in making a decision when making a diagnosis. The user sets the patient's existing symptoms, after which the managed data is processed. At the end, the user receives the result of the performed analysis with the most probable diagnosis to the least probable one with a calculated conformity assessment. Such a system has high efficiency, reliability, accessibility and productivity. The use of such a system allows you to avoid redundancy of information, thereby reducing the time for primary data processing
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