JOURNAL ARTICLE

A Contextual Ranking and Selection Method for Personalized Medicine.

  • Published In: Manufacturing & Service Operations Management (M&SOM) (INFORMS), 2024, v. 26, n. 1. P. 167 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Du, Jianzhong; Gao, Siyang; Chen, Chun-Hung 3 of 3

Abstract

The article focuses on developing simulation-based methods for personalized medicine (PM), which aims to select the best treatment tailored to each patient’s biometric context. It introduces three measures to evaluate the probability of correct treatment selection across contexts and demonstrates their asymptotic equivalence via a common convergence rate function. Two formulations are proposed to optimize simulation budget allocation for small and large context spaces, respectively, along with corresponding algorithms—CR&S Algorithm 1 for small-scale problems and CR&S Algorithm 2 for large-scale problems using linear models. Numerical experiments on benchmark functions and real-world PM cases, including cervical cancer prevention, show that these algorithms outperform existing methods by efficiently allocating simulation efforts to challenging context-treatment pairs, thereby improving decision quality under limited computational resources.

Additional Information

  • Source:Manufacturing & Service Operations Management (M&SOM) (INFORMS). 2024/01, Vol. 26, Issue 1, p167
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2024
  • ISSN:1523-4614
  • DOI:10.1287/msom.2022.0232
  • Accession Number:174952270
  • Copyright Statement:Copyright of Manufacturing & Service Operations Management (M&SOM) (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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