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

Miao He, Lei Zhao and Warren B. Powell

European Journal of Operational Research, 2012, vol. 222, issue 2, 328-340

Abstract: In the controlled ovarian hyperstimulation (COH) treatment, clinicians monitor the patients’ physiological responses to gonadotropin administration to tradeoff between pregnancy probability and ovarian hyperstimulation syndrome (OHSS). We formulate the dosage control problem in the COH treatment as a stochastic dynamic program and design approximate dynamic programming (ADP) algorithms to overcome the well-known curses of dimensionality in Markov decision processes (MDP). Our numerical experiments indicate that the piecewise linear (PWL) approximation ADP algorithms can obtain policies that are very close to the one obtained by the MDP benchmark with significantly less solution time.

Keywords: OR in health services; Approximate dynamic programming; Controlled ovarian hyperstimulation; Ovarian hyperstimulation syndrome (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:222:y:2012:i:2:p:328-340

DOI: 10.1016/j.ejor.2012.03.049

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