首页> 外文期刊>Journal of Theoretical and Applied Information Technology >WEB-EXPERT SYSTEM FOR THE DETECTION OF EARLY SYMPTOMS OF THE DISORDER OF PREGNANCY USING A FORWARD CHAINING AND BAYESIAN METHOD
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WEB-EXPERT SYSTEM FOR THE DETECTION OF EARLY SYMPTOMS OF THE DISORDER OF PREGNANCY USING A FORWARD CHAINING AND BAYESIAN METHOD

机译:前向链和贝叶斯方法的Web专家系统,用于检测妊娠障碍的早期症状

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Web-Expert system (Web-ES) is used to recognize the symptoms early in women pregnancy disorders. Every pregnancy risk factors will endanger the safety of the mother and the baby, if the information obtained is less in the treatment of pregnancy disorder. This study aims to build web-based expert systems (ES), such as a doctor or a patient to diagnose pregnancy in any place, so it can help women to know about the symptoms of pregnancy disorder. ES is analyzed using forward chaining (FC) method and the Bayesian theorems. One of the Techniques that has been used to make a decision tree, then does a search with FC and the calculation of the probability by Bayesian. Based on the selected input symptoms dataset used 35 patients, the results of a pregnancy disorder which have the highest risk of disruption in eclampsia, with a value of 97% and the suitability of 82.86% system accuracy. Subsequent research, we perform hybrid Bayesian theorem and FC with fuzzy-neural network environments to produce values higher accuracy and will also make a decision in group clinical results.
机译:Web专家系统(Web-ES)用于在女性妊娠疾病中及早识别症状。如果所获得的信息很少用于治疗妊娠失调,则每种怀孕的危险因素都会危及母亲和婴儿的安全。这项研究旨在建立诸如医生或患者之类的基于网络的专家系统(ES),以便在任何地方诊断妊娠,从而可以帮助女性了解妊娠疾病的症状。使用前向链接(FC)方法和贝叶斯定理分析ES。一种用于制作决策树的技术,然后使用FC进行搜索并通过贝叶斯方法进行概率计算。根据选择的输入症状数据集,使用了35位患者,这是一次妊娠子痫的结果,其子痫的破裂风险最高,诊断值为97%,系统准确度为82.86%。随后的研究中,我们在模糊神经网络环境中执行混合贝叶斯定理和FC,以产生更高的准确度值,并且还将决定组的临床结果。

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