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Applying reinforcement learning techniques to detect hepatocellular carcinoma under limited screening capacity

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  • Elliot Lee
  • Mariel Lavieri
  • Michael Volk
  • Yongcai Xu

Abstract

We investigate the problem faced by a healthcare system wishing to allocate its constrained screening resources across a population at risk for developing a disease. A patient’s risk of developing the disease depends on his/her biomedical dynamics. However, knowledge of these dynamics must be learned by the system over time. Three classes of reinforcement learning policies are designed to address this problem of simultaneously gathering and utilizing information across multiple patients. We investigate a case study based upon the screening for Hepatocellular Carcinoma (HCC), and optimize each of the three classes of policies using the indifference zone method. A simulation is built to gauge the performance of these policies, and their performance is compared to current practice. We then demonstrate how the benefits of learning-based screening policies differ across various levels of resource scarcity and provide metrics of policy performance. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Elliot Lee & Mariel Lavieri & Michael Volk & Yongcai Xu, 2015. "Applying reinforcement learning techniques to detect hepatocellular carcinoma under limited screening capacity," Health Care Management Science, Springer, vol. 18(3), pages 363-375, September.
    • Handle: RePEc:kap:hcarem:v:18:y:2015:i:3:p:363-375
    DOI: 10.1007/s10729-014-9304-0
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    References listed on IDEAS

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    1. Jagpreet Chhatwal & Oguzhan Alagoz & Elizabeth S. Burnside, 2010. "Optimal Breast Biopsy Decision-Making Based on Mammographic Features and Demographic Factors," Operations Research, INFORMS, vol. 58(6), pages 1577-1591, December.
    2. Turgay Ayer & Oguzhan Alagoz & Natasha K. Stout, 2012. "OR Forum---A POMDP Approach to Personalize Mammography Screening Decisions," Operations Research, INFORMS, vol. 60(5), pages 1019-1034, October.
    3. Aswin Dhamodharan & Ruben Proano, 2012. "Determining the optimal vaccine vial size in developing countries: a Monte Carlo simulation approach," Health Care Management Science, Springer, vol. 15(3), pages 188-196, September.
    4. Lisa M. Maillart & Julie Simmons Ivy & Scott Ransom & Kathleen Diehl, 2008. "Assessing Dynamic Breast Cancer Screening Policies," Operations Research, INFORMS, vol. 56(6), pages 1411-1427, December.
    5. Fatih Safa Erenay & Oguzhan Alagoz & Adnan Said, 2014. "Optimizing Colonoscopy Screening for Colorectal Cancer Prevention and Surveillance," Manufacturing & Service Operations Management, INFORMS, vol. 16(3), pages 381-400, July.
    6. Marion S. Rauner & Walter J. Gutjahr & Kurt Heidenberger & Joachim Wagner & Joseph Pasia, 2010. "Dynamic Policy Modeling for Chronic Diseases: Metaheuristic-Based Identification of Pareto-Optimal Screening Strategies," Operations Research, INFORMS, vol. 58(5), pages 1269-1286, October.
    7. Jingyu Zhang & Brian T. Denton & Hari Balasubramanian & Nilay D. Shah & Brant A. Inman, 2012. "Optimization of Prostate Biopsy Referral Decisions," Manufacturing & Service Operations Management, INFORMS, vol. 14(4), pages 529-547, October.
    8. H. Romero & N. Dellaert & S. Geer & M. Frunt & M. Jansen-Vullers & G. Krekels, 2013. "Admission and capacity planning for the implementation of one-stop-shop in skin cancer treatment using simulation-based optimization," Health Care Management Science, Springer, vol. 16(1), pages 75-86, March.
    9. Mehmet U. S. Ayvaci & Oguzhan Alagoz & Elizabeth S. Burnside, 2012. "The Effect of Budgetary Restrictions on Breast Cancer Diagnostic Decisions," Manufacturing & Service Operations Management, INFORMS, vol. 14(4), pages 600-617, October.
    10. Giovanni Parmigiani & Steven Skates & Marvin Zelen, 2002. "Modeling and Optimization in Early Detection Programs with a Single Exam," Biometrics, The International Biometric Society, vol. 58(1), pages 30-36, March.
    11. Sandra J. Lee & Marvin Zelen, 2008. "Mortality Modeling of Early Detection Programs," Biometrics, The International Biometric Society, vol. 64(2), pages 386-395, June.
    12. Yue Zhang & Martin Puterman, 2013. "Developing an adaptive policy for long-term care capacity planning," Health Care Management Science, Springer, vol. 16(3), pages 271-279, September.
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    Cited by:

    1. Gong, Jue & Liu, Shan, 2023. "Partially observable collaborative model for optimizing personalized treatment selection," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1409-1419.

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