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Developing a Fuzzy Expert System to Predict the Risk of Neonatal Death
Reza Safdari1, Maliheh Kadivar2, Mostafa Langarizadeh3
1Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.
Introduction:
This study aims at developing a fuzzy expert system to predict the possibility of neonatal death.
Materials And Methods:
A questionnaire was given to Iranian neonatologists and the more important factors were identified based on their answers. Then, a computing model was designed considering the fuzziness of variables having the highest neonatal mortality risk. The inference engine used was Mamdani's method and the output was the risk of neonatal death given as a percentage. To validate the designed system, neonates' medical records real data at a Tehran hospital were used. MATLAB software was applied to build the model, and user interface was developed by C# programming in Visual Studio platform as bilingual (English and Farsi user interface).
Results:
According to the results, the accuracy, sensitivity, and specificity of the model were 90%, 83% and 97%, respectively.
Conclusion:
The designed fuzzy expert system for neonatal death prediction showed good accuracy as well as proper specificity, and could be utilized in general hospitals as a clinical decision support tool.
