Artificial intelligence for optimal anemia management in end-stage renal disease

被引：16

作者：

Brier, Michael E. ^{[1
]}

Gaweda, Adam E. ^{[1
]}

机构：

[1] Univ Louisville, Dept Med, Div Nephrol & Hypertens, Louisville, KY 40292 USA

来源：

KIDNEY INTERNATIONAL | 2016年 / 90卷 / 02期

关键词：

HEMODIALYSIS-PATIENTS; ALPHA; MODEL;

D O I：

10.1016/j.kint.2016.05.018

中图分类号：

R5 [内科学]; R69 [泌尿科学（泌尿生殖系疾病）];

学科分类号：

1002 ; 100201 ;

摘要：

Computational intelligence for the prediction of hemoglobin to guide the selection of erythropoiesis-stimulating agent dose results in improved anemia management. The models used for the prediction result from the use of individual patient data and help to increase the number of hemoglobin observations within the target range. The benefits of using these modeling techniques appear to be a decrease in erythropoiesis-stimulating agent use and a decrease in the number of transfusions. This study confirms the results of previous smaller studies and suggests that additional beneficial results may be achieved.

引用

页码：259 / 261

页数：4

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