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MEDICAL TREATMENT METRIC MODELLING BASED ON MACHINE LEARNING

机译:基于机器学习的医学治疗度量模型

摘要

In one example, an apparatus comprises a treatment metric model database that stores a plurality of treatment metric models, each of the plurality of treatment metric models being generated for a first cluster of cluster features vectors, each cluster feature vector representing a distribution for each of a plurality of data categories of patients data represented by patient feature vectors clustered in a second cluster. The apparatus is further configured to: receive patient characteristics features data of a patient; identify a first treatment metric model based on the patient characteristics features data of the patient; input the first patient characteristic features data and data representing a range of administrations of the treatment to the first treatment metric model to compute a range of the treatment metric; and select an administration of the treatment from the range of administrations of the treatment having optimal treatment metric.
机译:在一个示例中,一种设备包括治疗度量模型数据库,该数据库存储了多个治疗度量模型,所述多个治疗度量模型中的每一个都是针对第一集群特征向量集群生成的,每个集群特征向量代表每个集群特征向量的分布。由患者特征向量表示的患者数据的多个数据类别聚集在第二群集中。该设备还被配置为:接收患者的患者特征特征数据;以及基于患者的患者特征数据来识别第一治疗度量模型;将第一患者特征特征数据和代表治疗范围的数据输入到第一治疗度量模型以计算治疗度量的范围;并从具有最佳治疗指标的治疗给药范围中选择治疗给药。

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