Development of medical diagnostic decision support systems and their economic efficiency
Journal Title: Технологический аудит и резервы производства - Year 2018, Vol 2, Issue 2
Abstract
<p><em>The object of research is the diagnostic decision support system (DSS). One of the most problematic areas in medical diagnostic systems is the formation of a knowledge base based on expert rules, which provides a recommendation for the disease. The methods of designing medical diagnostic systems have been studied. Methods for applying the potential of artificial intelligence in medicine in the form of fuzzy rules or conducting diagnostics on the basis of Bayesian networks are considered. Intellectual computing tools in the form of expert systems based on rules and fuzzy logic, applied to neural networks and genetic algorithms performed in medical diagnostics are considered.</em></p><p><em>To develop a decision support system for a pediatrician, a method to build a knowledge base on the basis of logical rules «If ..., then ...» was chosen. Using this method allows to create initial conditions for input data in the system, and speed up their processing in the knowledge base. Although the knowledge base is quite cumbersome, this does not reduce the performance of the system.</em></p><p><em>In the process of research, the development of a medical diagnostic system for decision support by a pediatrician for the design stages is described. The application of this system allows to automate the process of document circulation for a pediatrician and to speed up the stage of preliminary assessment of the patient's condition.</em></p><p><em>The built-in pediatrician electronic pediatric module not only automates the workflow process, reduces the doctor's work time with papers, but also allows to obtain complete information about the patient.</em></p><p><em>The calculation of economic efficiency from the DSS introduction by a pediatrician is performed. The system cost is to be recouped within 1 year.</em></p><p><em>The prospect of adding modules to the system for individual diseases and forming an electronic record from the moment of birth with the prospect of transferring data to the system for adults are advantages over analogues of this software product.</em></p>
Authors and Affiliations
Olga Kravchenko
Keywords
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- EP ID EP527365
- DOI 10.15587/2312-8372.2018.128455
- Views 136
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