Decision support system for prediction and diagnosis of endometritis in the postpartum period

The purpose of the research is to develop a decision support system for gynecologists, based on synthesized prognostic and diagnostic decision rules, which will be used in the diagnosis and prognosis of postpartum endometritis.

Methods. The following tools were used in the development of the decision support system: medical statistics, expert system development methods, decision theory, and pattern recognition methods. Such tools for statistical data analysis as Excel and Statistica were used to process and analyze medical data, as well as to verify crucial diagnostic rules. To assess the risk of postpartum endometritis and its diagnosis, 31 signs are included, ranked according to their degree of informativeness. These data were used as the basis for the development of an algorithm for predicting the risk of developing postpartum endometritis in a decision support system.

Results. The application of the developed diagnostic decision rules on clinically representative material showed a diagnostic effectiveness of 0,96±0,02. The developed expert system can be effectively applied in clinical conditions. It is also possible to use this expert system in the educational process when training medical professionals.

Conclusion. Consideration of risk factors, integration of data from various sources, the use of prognostic models and the formation of individual recommendations for treatment and prevention are all key aspects that should be taken into account when developing such a system. The introduction of such a system into clinical practice can significantly improve the quality of diagnosis and treatment of postpartum endometritis, reduce the risk of complications and improve patient outcomes.

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