Developing a Fuzzy Expert System to Predict the Risk of Neonatal Death

Developing a Fuzzy Expert System to Predict the Risk of Neonatal Death Publisher

Safdari R¹ ; Kadivar M² ; Langarizadeh M³ ; Nejad AF¹ ; Kermani F¹

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1. Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
2. Department of Neonatology, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
3. Department of Health Information Management, School of Health Management and Information Science, Iran University of Medical Sciences, Tehran, Iran

Source: Acta Informatica Medica Published:2016

Abstract

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. ©2016 Reza Safdari, Maliheh Kadivar, Mostafa Langarizadeh, Ahmadreaza Farzaneh Nejad, Farzaneh Kermani.

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Hojjat Zeraati (1)

Reza Safdari (1)

Style	Citing Format
MLA	Safdari R, et al.. "Developing a Fuzzy Expert System to Predict the Risk of Neonatal Death." Acta Informatica Medica, vol. 24, no. 1, 2016, pp. 34-37.
APA	Safdari R, Kadivar M, Langarizadeh M, Nejad AF, Kermani F (2016). Developing a Fuzzy Expert System to Predict the Risk of Neonatal Death. Acta Informatica Medica, 24(1), 34-37.
Chicago	Safdari R, Kadivar M, Langarizadeh M, Nejad AF, Kermani F. "Developing a Fuzzy Expert System to Predict the Risk of Neonatal Death." Acta Informatica Medica 24, no. 1 (2016): 34-37.
Harvard	Safdari R et al. (2016) 'Developing a Fuzzy Expert System to Predict the Risk of Neonatal Death', Acta Informatica Medica, 24(1), pp. 34-37.
Vancouver	Safdari R, Kadivar M, Langarizadeh M, Nejad AF, Kermani F. Developing a Fuzzy Expert System to Predict the Risk of Neonatal Death. Acta Informatica Medica. 2016;24(1):34-37.
BibTex	@article{ author = {Safdari R and Kadivar M and Langarizadeh M and Nejad AF and Kermani F}, title = {Developing a Fuzzy Expert System to Predict the Risk of Neonatal Death}, journal = {Acta Informatica Medica}, volume = {24}, number = {1}, pages = {34-37}, year = {2016} }
RIS	TY - JOUR AU - Safdari R AU - Kadivar M AU - Langarizadeh M AU - Nejad AF AU - Kermani F TI - Developing a Fuzzy Expert System to Predict the Risk of Neonatal Death JO - Acta Informatica Medica VL - 24 IS - 1 SP - 34 EP - 37 PY - 2016 ER -

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