医学方面的翻译,高手速进
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发布时间：2022-04-23 06:02
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时间：2023-09-28 20:57
Machine learning methods are being used in genomics, pro- teomics, microarrays, system biology evolution, and text min- ing (7). However, this is the first time that they have been applied to validation of antifungal breakpoints. The 90-60 rule has defined the accuracy of antimicrobial susceptibility testing for predicting the outcome of bacterial infections. This rule was adopted by mycologists because the clinical correlation studies analyzed showed similar predictive patterns (10).
机器学习方法正广泛应用于基因组学，蛋白质组学，基因芯片，系统生物进化学，和文本挖掘(文献7)。然而，此方法却是第一次应用于抗真菌临界点验证。90-60准则界定了细菌*染的药敏试验的预测结果准确性。因为其临床相关性研究分析与预测模式相符合，此规则多用于真菌学实验。然而，患者结果的MIC值或与效学参数的相关性应具备与那些使用任何诊断工具做出的实验结果相似的统计评估。机器学习方法展现了一个使用统计理论与数据集建立一个实验模型的可能性。
How- ever, the correlation of MIC values or pharmacodynamic pa- rameters with patient outcome should include statistical eval- uations similar to those used with any diagnostic tool. Machine learning methods represent an opportunity to use statistical theory for building a model using a data set. However, it is crucial to find the optimal solution; to achieve such a solution, several classifiers must be employed for comparisons of the models obtained with each one. In this work, five classifiers (J48, CART, OneR, Naïve Bayes, and Simple Logistic) were compared to identify which values for MIC or dose/MIC split the populations of successes and failures. The statistical power of each model has been evaluated by means of analyses of the sensitivity, specificity, false-positive rate, area under the ROC curve, and MCC index.
不过，最关键一定的还是要找到最佳的解决方案；要实现这样一个解决办法，必须使用多个分类方法以通过各自的结果作出模型对比研究。在这项工作中，五个分类器(J48、CART、OneR、朴素贝叶斯，简单线性回归)进行比较，以确定哪些值MIC或dose/MIC对于人群的治疗成功与失败的分划最为可靠。每个模型的统计功效应由敏感性，特异性，假阳性率，ROC曲线下面积，和MCC指数等分析手段来评判。
The classifiers choose the MIC that best split the popula- tions of successes and failures. This value is presented as mg/liter for successes and x mg/liter for failures. However, breakpoints usually have three categories, namely, susceptible, intermediate (with susceptibility dependent on dose level), and resistant, presented as mg/liter for susceptible isolates, x and y mg/liter for intermediate isolates, and y mg/liter for resistant isolates. The definition for the intermediate category implies that an infection e to the isolate may be appropri- ately treated in body sites where the drugs are physically con- centrated or when a high dosage of drug can be used. It also indicates a buffer zone that should prevent small, uncontrolled, technical factors from causing major discrepancies in interpre- tations. The main target of any susceptibility testing is to iden- tify resistant strains or, in other words, to identify the drugs that are less likely to eradicate the infection (14).
分类法应选择可以最正确地界定失败与成功临界点人群分划的MIC值。这个值要以成功值为MIC <= w mg/liter， 失败值为MIC <= w mg/liter的形式来表示。然临界点通常分为3类，易感、中度(其感染性因剂量而异)、抗感。其区间分别表示为：易感为 <=w mg/liter, 中度为 >x且<y mg/liter，抗感为>y mg/liter。对中度类的定义意味着，菌落感染的治疗可以适当的通过在个别物理位置采取集中治疗，适当时候可以使用高剂量。这也表明了有一个缓冲区间来预防一些微小的、不可控制、技术上的因素而导致的重大差异。敏感性测试的主要目的是查明耐药菌株，或者说是找出那些不太容易根除感染的药物(文献14)。
