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Cited by in F6Publishing
For: Yaesoubi R, Cohen T. Identifying cost-effective dynamic policies to control epidemics. Stat Med 2016;35:5189-209. [PMID: 27449759 DOI: 10.1002/sim.7047] [Cited by in Crossref: 7] [Cited by in F6Publishing: 9] [Article Influence: 1.0] [Reference Citation Analysis]
Number Citing Articles
1 Nguyen QD, Prokopenko M. A general framework for optimising cost-effectiveness of pandemic response under partial intervention measures. Sci Rep 2022;12:19482. [PMID: 36376551 DOI: 10.1038/s41598-022-23668-x] [Reference Citation Analysis]
2 Guo X, Chen P, Liang S, Jiao Z, Li L, Yan J, Huang Y, Liu Y, Fan W. PaCAR: COVID-19 Pandemic Control Decision Making via Large-Scale Agent-Based Modeling and Deep Reinforcement Learning. Med Decis Making 2022;:272989X221107902. [PMID: 35775610 DOI: 10.1177/0272989X221107902] [Reference Citation Analysis]
3 Demirbilek M. Benzetim tabanlı adaptif aşı dağıtım stratejisi. GUMMFD 2022. [DOI: 10.17341/gazimmfd.758346] [Reference Citation Analysis]
4 Madni AM, Augustine N, Madni C, Sievers M. Multi-model-Based Decision Support in Pandemic Management. Handbook of Model-Based Systems Engineering 2022. [DOI: 10.1007/978-3-030-27486-3_67-1] [Reference Citation Analysis]
5 Skarp JE, Downey LE, Ohrnberger JWE, Cilloni L, Hogan AB, Sykes AL, Wang SS, Shah HA, Xiao M, Hauck K. A Systematic Review of the Costs Relating to Non-pharmaceutical Interventions Against Infectious Disease Outbreaks. Appl Health Econ Health Policy 2021;19:673-97. [PMID: 34114184 DOI: 10.1007/s40258-021-00659-z] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.5] [Reference Citation Analysis]
6 Yaesoubi R, Havumaki J, Chitwood MH, Menzies NA, Gonsalves G, Salomon JA, Paltiel AD, Cohen T. Adaptive Policies to Balance Health Benefits and Economic Costs of Physical Distancing Interventions during the COVID-19 Pandemic. Med Decis Making 2021;41:386-92. [PMID: 33504258 DOI: 10.1177/0272989X21990371] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
7 Libin PJK, Moonens A, Verstraeten T, Perez-sanjines F, Hens N, Lemey P, Nowé A. Deep Reinforcement Learning for Large-Scale Epidemic Control. Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track 2021. [DOI: 10.1007/978-3-030-67670-4_10] [Cited by in Crossref: 5] [Article Influence: 2.5] [Reference Citation Analysis]
8 Sy CL, Aviso KB, Cayamanda CD, Chiu ASF, Lucas RIG, Promentilla MAB, Razon LF, Tan RR, Tapia JFD, Torneo AR, Ubando AT, Yu DEC. Process integration for emerging challenges: optimal allocation of antivirals under resource constraints. Clean Technol Environ Policy 2020;:1-12. [PMID: 32837502 DOI: 10.1007/s10098-020-01876-1] [Cited by in Crossref: 4] [Cited by in F6Publishing: 5] [Article Influence: 1.3] [Reference Citation Analysis]
9 Shearer FM, Moss R, McVernon J, Ross JV, McCaw JM. Infectious disease pandemic planning and response: Incorporating decision analysis. PLoS Med 2020;17:e1003018. [PMID: 31917786 DOI: 10.1371/journal.pmed.1003018] [Cited by in Crossref: 47] [Cited by in F6Publishing: 42] [Article Influence: 15.7] [Reference Citation Analysis]
10 Yaesoubi R, Cohen T. ADAPTIVE DECISION-MAKING DURING EPIDEMICS. Decision Analytics and Optimization in Disease Prevention and Treatment 2018. [DOI: 10.1002/9781118960158.ch3] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.2] [Reference Citation Analysis]