A Simulation Optimization Approach forPrecision Medicine

Jianzhong Du (), Siyang Gao and Chun-Hung Chen
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Jianzhong Du: City University of Hong Kong
Siyang Gao: City University of Hong Kong
Chun-Hung Chen: George Mason University

A chapter in AI and Analytics for Public Health, 2022, pp 281-289 from Springer

Abstract: Abstract In this research, we consider the emerging problem of precision medicine (PM) in healthcare. We use the tool of simulation to evaluate the performance of feasible treatment methods and make tailored treatment decision for the patients. While simulation enables us to model complex, personalized, and stochastic behaviours, efficiency is still a big concern. To address the computational challenge of conducting simulation experiments, we formulate the PM problem into Ranking and Selection in the presence of covariates and propose an efficient and simple algorithm that can be proven to achieve the optimal allocation for PM asymptotically. A PM case study built from real-world data in the literature shows when compared with the traditional practice for solving PM problems by simulation, the new algorithm can significantly save computational resources.

Keywords: Precision medicine; Ranking and selection; Simulation optimization (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-030-75166-1_20

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DOI: 10.1007/978-3-030-75166-1_20

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