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本文根据恶性疟疾发作成脑型疟疾的可能先兆信息,探讨应用模糊集理论预测脑型疟疾的发作。先后共统计分析了自1973年以来见诸报道和我科收治的2200多例恶性疟疾和1300多例脑型疟疾,选择了甲皱微循环观察、血液流变学检测及临床一般项目等三类12项指标作为预测的先兆信息,并依据频率比法确定出各项指标的权系数,建立预测脑型疟疾发作的Fuzzy数学模型及各子集的隶属函数与发病隶属度并确定预测阈值。该阈值对我科1989年收治102例恶性疟疾(其中含脑型疟7例)进行检证。结果假阴性率β=0,假阳性率α=0.091,诊断(正确率)指数J=1-α-β=0.909。此法对预测恶性疟疾发作成脑型疟提供了新的可靠方法。
Based on the possible aura of cerebral malaria caused by the onset of falciparum malaria, this paper explores the application of fuzzy set theory to predict the onset of cerebral malaria. A total of more than 2200 cases of malaria and more than 1300 cases of cerebral malaria have been reported and analyzed since 1973, covering a total of more than 1,300 cases of cerebral malaria. A total of three categories of nail fold microcirculation observation, hemorheology and clinical general projects were selected 12 indicators as a precursor to the prediction, and according to the frequency ratio method to determine the weight coefficient of each indicator to establish the Fuzzy mathematical model predicting the onset of cerebral malaria and membership function of each subset and incidence membership and to determine the prediction threshold. The threshold of our department in 1989 admitted 102 cases of malignant malaria (including cerebral malaria in 7 cases) for verification. Results False negative rate β = 0, false positive rate α = 0.091, diagnostic (accuracy rate) index J = 1-α-β = 0.909. This method provides a new reliable method of predicting the onset of cerebral malaria from falciparum malaria.