Fuzzy expert system in the prediction of neonatal resuscitation
Fuzzy expert system in the prediction of neonatal resuscitation
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DOI：
10.1590/s0100-879x2004000500018
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发表时间：
2004-05-01
影响因子：
2.3
通讯作者：
Silveira, P.S.P.
中科院分区：
文献类型：
--
作者：
Reis, M.A.M.;Ortega, N.R.S.;Silveira, P.S.P.
鉴于预测医学中发生的危急情况的重要性，我们建议使用一个模糊专家系统来预测需要先进的新生儿复苏努力在产房。该系统将产妇的医疗、产科和新生儿特征与新生儿的临床状况联系起来，提供了一种需要先进新生儿复苏措施的风险衡量方法。它的结构是一个模糊的组成开发的基础上的主观认识的危险，9个产科医生面临61产前和分娩时的临床情况，提供一定程度的关联发生围产期窒息的风险。由此产生的关系矩阵描述了临床因素和围产期窒息的风险之间的关联。分析所有61个临床因素的存在或不存在的输入，系统返回围产期窒息的风险率作为输出。一个前瞻性收集的系列304例围产期保健进行了分析，以确定系统的性能。模糊专家系统提出了一个灵敏度为76.5%，特异性为94.8%，在识别需要先进的新生儿复苏措施，考虑到截止值为5的规模从0到10。受试者工作特征曲线下面积为0.93。风险情况的识别在卫生保健规划中发挥着重要作用。这些初步结果鼓励我们开展进一步的研究，并完善这一模式，这是为了实施一个辅助系统，能够帮助卫生保健工作人员在围产期护理决策。
In view of the importance of anticipating the occurrence of critical situations in medicine, we propose the use of a fuzzy expert system to predict the need for advanced neonatal resuscitation efforts in the delivery room. This system relates the maternal medical, obstetric and neonatal characteristics to the clinical conditions of the newborn, providing a risk measurement of need of advanced neonatal resuscitation measures. It is structured as a fuzzy composition developed on the basis of the subjective perception of danger of nine neonatologists facing 61 antenatal and intrapartum clinical situations which provide a degree of association with the risk of occurrence of perinatal asphyxia. The resulting relational matrix describes the association between clinical factors and risk of perinatal asphyxia. Analyzing the inputs of the presence or absence of all 61 clinical factors, the system returns the rate of risk of perinatal asphyxia as output. A prospectively collected series of 304 cases of perinatal care was analyzed to ascertain system performance. The fuzzy expert system presented a sensitivity of 76.5% and specificity of 94.8% in the identification of the need for advanced neonatal resuscitation measures, considering a cut-off value of 5 on a scale ranging from 0 to 10. The area under the receiver operating characteristic curve was 0.93. The identification of risk situations plays an important role in the planning of health care. These preliminary results encourage us to develop further studies and to refine this model, which is intended to implement an auxiliary system able to help health care staff to make decisions in perinatal care.