英语翻译All classifiers were able to yield a predictive model for the OPC data set.The CART method gave the best statistical power for a MIC 4 mg/liter for detecting failures,although the rest of classifiers also exhibited high statistical power

英语翻译All classifiers were able to yield a predictive model for the OPC data set.The CART method gave the best statistical power for a MIC 4 mg/liter for detecting failures,although the rest of classifiers also exhibited high statistical power
英语翻译
All classifiers were able to yield a predictive model for the OPC data set.The CART method gave the best statistical power for a MIC 4 mg/liter for detecting failures,although the rest of classifiers also exhibited high statistical power (Ta- ble 1).However,for candidemia the scenario was completely different.CART and Naïve Bayes methods were able to dis- cover a MIC value that split the populations,but the statistical power was limited (although it was slightly better for CART).Regarding dose/MIC targets,results were similar for the OPC data set.All classifiers were able to determine a dose/ MIC value that split the populations of successes and failures,with areas under the ROC curves above 0.85.However,for candidemia,only CART produced the same dose/MIC value as that determined for the OPC data set,but the CART deter-
mination had little statistical power (Table 2).
The determinations for the two cohorts had different values with respect to statistical power,and this merits an explana- tion.For the OPC cohort,85 cases had a MIC 4 mg/liter,but there were only 4 cases for candidemia that showed this value.The lack of strains with MIC 4 mg/liter in the candidemia cohort explains the limited statistical power of the models.However,the models for the OPC and candidemia datasets gave the same values for MIC and for dose/MIC for at least one classifier.Therefore,the results obtained for the whole data set can be considered if the models produce the same MIC or dose/MIC when the datasets are analyzed separately,despite candidemia and OPC representing quite different clin- ical situations.If several models satisfy this circumstance,the statistical power of the analyses must be taken into account.
The CART model produced identical target values for the two datasets and the highest statistical power in satisfying both sets of circumstances.The CART model gave a MIC 4 mg/liter as the breakpoint of resistance,with a sensitivity of
87%,a false-positive rate of 8%,an area under the ROC curve of 0.89,and an MCC index of 0.80 (Table 1).In addition,a dose/MIC 75 is proposed as the target to achieve treatment success.This means that a fluconazole dose of 400 mg/day will cover all strains with a fluconazole MIC of 4 mg/liter or less.The sensitivity of this target is 91%,with a false-positive rate of
10%,an area under the ROC curve of 0.90,and an MCC index of 0.80 (Table 2).

英语翻译All classifiers were able to yield a predictive model for the OPC data set.The CART method gave the best statistical power for a MIC 4 mg/liter for detecting failures,although the rest of classifiers also exhibited high statistical power
All classifiers were able to yield a predictive model for the OPC data set.The CART method gave the best statistical power for a MIC 4 mg/liter for detecting failures,although the rest of classifiers also exhibited high statistical power (Ta- ble 1).However,for candidemia the scenario was completely different.CART and Naïve Bayes methods were able to dis- cover a MIC value that split the populations,but the statistical power was limited (although it was slightly better for CART).Regarding dose/MIC targets,results were similar for the OPC data set.All classifiers were able to determine a dose/ MIC value that split the populations of successes and failures,with areas under the ROC curves above 0.85.However,for candidemia,only CART produced the same dose/MIC value as that determined for the OPC data set,but the CART determination had little statistical power (Table 2).
　　所有的分类都能够产生一个预测模型的OPC数据集.尽管其他分类法的统计功效也相当高,但其中Cart的方法在MIC > 4mg /liter的情况下的失败预测具有最佳统计功效(表1).然而对于念珠菌的情况完全不同.CART和朴素贝叶斯方法能够找到良好MIC值来分划人群,但统计功效却很有限(其中CART略强一些).对于dose/MIC的目标值,结果与OPC人群实验数据集结果相似.所有分类法都能够确定可以以成功与失败来分划人群的dose/ MIC,其相应的ROC曲线面积为0.85.然而对于念珠菌,只有CART生成了相同的dose/MIC决定值,但具有很低的统计功效.
　　The determinations for the two cohorts had different values with respect to statistical power,and this merits an explana- tion.For the OPC cohort,85 cases had a MIC 4 mg/liter,but there were only 4 cases for candidemia that showed this value.The lack of strains with MIC 4 mg/liter in the candidemia cohort explains the limited statistical power of the models.However,the models for the OPC and candidemia datasets gave the same values for MIC and for dose/MIC for at least one classifier.Therefore,the results obtained for the whole data set can be considered if the models produce the same MIC or dose/MIC when the datasets are analyzed separately,despite candidemia and OPC representing quite different clin- ical situations.If several models satisfy this circumstance,the statistical power of the analyses must be taken into account.
　　值得解释的是,两个病例群体的区间分划具有不同的预测值和统计功效.对于患有OPC的病例,85例的MIC > 4 mg/liter,但念珠菌患者中这样的病例只有4例.念珠菌患者中MIC > 4 mg/liter 群体的缺乏解释了统计功效的局限性.
　　然而,OPC和念珠菌患者群体数据模型得出的MIC以及dose/MIC的值在至少一种分类法下的结果是相同的.因此,若分别研究的数据却产生了相同的MIC或dose/MIC值,那么急事OPC与念珠菌血病代表着截然不同的临床情况,但是所有总体仍然可以合并考虑.在整个数据集得到的结果可以认为如果模型产生同样的MIC或剂量/麦克风时,数据集分别进行了分析,尽管念珠菌,代表完全不同的临床情况下的OPC.如果几个模型都满足同一情形,则此时必须考虑分析的统计功效.
　　The CART model produced identical target values for the two datasets and the highest statistical power in satisfying both sets of circumstances.The CART model gave a MIC 4 mg/liter as the breakpoint of resistance,with a sensitivity of 87%,a false-positive rate of 8%,an area under the ROC curve of 0.89,and an MCC index of 0.80 (Table 1).In addition,a dose/MIC 75 is proposed as the target to achieve treatment success.This means that a fluconazole dose of 400 mg/day will cover all strains with a fluconazole MIC of 4 mg/liter or less.The sensitivity of this target is 91%,with a false-positive rate of 10%,an area under the ROC curve of 0.90,and an MCC index of 0.80 (Table 2).
　　CART模型下两个数据集产生的目标值相同,且在两种情形下的统计功效均为最高.CART模型给出的抗感临界点MIC > 4 mg/liter,此时敏感度87%,假阳性率为8%,ROC曲线下面积0.89,MCC系数为0.80(表1).此外,评判成功治疗的目标指标一般认定为dose/MIC > 75.这意味着400 mg/天的氟康唑剂量将覆盖MIC值为4mg/liter及以下的所有菌株.这一目标的敏感度为91%,假阳性率10%,ROC曲线下面积为0.90,MCC指数为0.80 (表2).