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

Abstract

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.