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Thalassemia, Vietnamese population, clinical decision support system, expert system, AI-based system
Background and objectives. Investigating the prevalence of thalassemia in the Vietnamese population, building a clinical decision support system for prenatal screening for thalassemia.
Methods. A cross-sectional study was conducted on pregnant women and their husbands visiting Vietnam National Hospital of Obstetrics and Gynecology from October 2020 to December 2021.
Results. The clinical decision support system including 2 different types of systems for prenatal screening for thalassemia (expert system and 4 AI-based CDSS) was built. Accuracy of expert system and AI-based CDSS was compared. The rate of patients with Alpha thalassemia is 10.73%, the rate of patients with beta-thalassemia is 2.24%, and 0.29% of patients carry both alpha-thalassemia and beta-thalassemia gene mutations. The expert system showed an accuracy of 98.45%. Among the AI-based CDSS developed, the MLP model was the most stable regardless of the training database.
Conclusions. When comparing the expert system with the AI-based CDSS, the accuracy of the expert system and AI-based models was found to be comparable. The developed expert system for prenatal thalassemia screening showed high accuracy. AI-based CDSS showed satisfactory results and can be applied in clinical practice.
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