کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9653143 | 677478 | 2005 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Individualization of pharmacological anemia management using reinforcement learning
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Effective management of anemia due to renal failure poses many challenges to physicians. Individual response to treatment varies across patient populations and, due to the prolonged character of the therapy, changes over time. In this work, a Reinforcement Learning-based approach is proposed as an alternative method for individualization of drug administration in the treatment of renal anemia. Q-learning, an off-policy approximate dynamic programming method, is applied to determine the proper dosing strategy in real time. Simulations compare the proposed methodology with the currently used dosing protocol. Presented results illustrate the ability of the proposed method to achieve the therapeutic goal for individuals with different response characteristics and its potential to become an alternative to currently used techniques.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neural Networks - Volume 18, Issues 5â6, JulyâAugust 2005, Pages 826-834
Journal: Neural Networks - Volume 18, Issues 5â6, JulyâAugust 2005, Pages 826-834
نویسندگان
Adam E. Gaweda, Mehmet K. Muezzinoglu, George R. Aronoff, Alfred A. Jacobs, Jacek M. Zurada, Michael E. Brier,