Bellazzi R
Dpt. Informatica e Sistemistica, Universitá di Pavia, Italy.
Proc Annu Symp Comput Appl Med Care. 1992:572-8.
This paper describes how Bayesian Networks can be used in combination with compartmental models to plan Recombinant Human Erythropoietin (r-HuEPO) delivery in the treatment of anemia of chronic uremic patients. Past measurements of hematocrit or hemoglobin concentration in a patient during the therapy can be exploited to adjust the parameters of a compartmental model of the erythropoiesis. This adaptive process allows more accurate patient-specific predictions, and hence a more rational dosage planning. We describe a drug delivery optimization protocol, based on our approach. Some results obtained on real data are presented.
本文描述了如何将贝叶斯网络与房室模型相结合，用于规划重组人促红细胞生成素（r-HuEPO）给药，以治疗慢性尿毒症患者的贫血。治疗期间患者过去的血细胞比容或血红蛋白浓度测量值可用于调整红细胞生成房室模型的参数。这种自适应过程可以实现更准确的患者特异性预测，从而制定更合理的剂量规划。我们基于我们的方法描述了一种药物递送优化方案。还展示了一些基于实际数据获得的结果。
