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Original ArticleOpen Access
Development of a Medical Expert System for the Diagnosis of Ectopic Pregnancy
Kitporntheranunt M 
,
Wiriyasuttiwong W
,
Wiriyasuttiwong W Objective: To developed a software-based medical expert system for supporting in the diagnosis of ectopic
pregnancy.
Material and Method: This system was developed to facilitate the knowledge creation and inference engine.
The diagnostic process used the interactive backward chaining inference algorithm. The medical knowledge
base was represented as production rules which performed in tree structure. The system designed to interact
with users in question information form. After that, the clinical data from medical records of patients were
applied to the system by physician retrospectively.
Results: Thirty-two medical records of women who diagnosed ectopic pregnancy were reviewed. The mean
patients’ age was 27.7 years. The majority of the patients were multigravida gestation. There were twenty-one
patients who did not have any risk factors of ectopic pregnancy. 31 of patients’ clinical data applied to the
system successfully. All of them had correspondent diagnosis with established ectopic pregnancy.
Conclusion: This medical expert system was found to be a good tool to facilitate the decision making in the
diagnosis of ectopic pregnancy.
Keywords: Medical expert system, Ectopic pregnancy, Medical knowledge-based system
pregnancy.
Material and Method: This system was developed to facilitate the knowledge creation and inference engine.
The diagnostic process used the interactive backward chaining inference algorithm. The medical knowledge
base was represented as production rules which performed in tree structure. The system designed to interact
with users in question information form. After that, the clinical data from medical records of patients were
applied to the system by physician retrospectively.
Results: Thirty-two medical records of women who diagnosed ectopic pregnancy were reviewed. The mean
patients’ age was 27.7 years. The majority of the patients were multigravida gestation. There were twenty-one
patients who did not have any risk factors of ectopic pregnancy. 31 of patients’ clinical data applied to the
system successfully. All of them had correspondent diagnosis with established ectopic pregnancy.
Conclusion: This medical expert system was found to be a good tool to facilitate the decision making in the
diagnosis of ectopic pregnancy.
Keywords: Medical expert system, Ectopic pregnancy, Medical knowledge-based system
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