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

Miao He, Lei Zhao, Warren Buckler Powell

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)328-340
Number of pages13
JournalEuropean Journal of Operational Research
Volume222
Issue number2
DOIs
StatePublished - Oct 16 2012

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

Keywords

  • Approximate dynamic programming
  • Controlled ovarian hyperstimulation
  • OR in health services
  • Ovarian hyperstimulation syndrome

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