Approximate dynamic programming algorithms for optimal dosage decisions in controlled ovarian hyperstimulation

► Model the dosage decisions in COH treatment as a stochastic optimization problem. ► Design efficient approximate dynamic programming (ADP) solution algorithms. ► Compare ADP policies with the Markov decision processes (MDP) benchmark. ► Apply cutting-edge OR in evidence-based and data-driven clini...

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Vydané v:	European journal of operational research Ročník 222; číslo 2; s. 328 - 340
Hlavní autori:	He, Miao, Zhao, Lei, Powell, Warren B.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier B.V 16.10.2012 Elsevier Elsevier Sequoia S.A
Predmet:	Algorithms Applied sciences Approximate dynamic programming Approximation Biological and medical sciences Controlled ovarian hyperstimulation Decision theory. Utility theory Decisions Dosage Dynamic programming Endocrinopathies Exact sciences and technology Hypothalamus. Hypophysis. Epiphysis (diseases) Markov analysis Markov processes Mathematical analysis Mathematical programming Mathematics Medical sciences Medical treatment Monitors Non tumoral diseases. Target tissue resistance. Benign neoplasms Operational research and scientific management Operational research. Management science Optimization Optimization algorithms OR in health services Ovarian hyperstimulation syndrome Ovaries Probability and statistics Probability theory and stochastic processes Sciences and techniques of general use Studies Approximate dynamic programming Ovarian hyperstimulation syndrome Controlled ovarian hyperstimulation OR in health services Dimensionality Markov decision Probabilistic approach Optimal algorithm Hospital management Gonadotropin Approximation algorithm Experimental study Stochastic programming Assay Pregnancy Optimal decision Linear approximation Physiology Dynamic programming Piecewise linearization Piecewise-linear techniques
ISSN:	0377-2217, 1872-6860
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