Disease Classification in Health Care Systems With Game Theory Approach

There are numerous cases in real life when we come across problems involving the optimization of multiple objectives simultaneously. One of the complexities of solving such problems is that often one or more objectives are usually conflicting under given conditions. In this study, the benefits of relying on a deployed Clinical Decision Support System (CDSS) concerning the overall reputation of a health facility has been studied. The analysis is performed in terms of a co-operative Bayesian game-theoretic model. The game is played between two players of which the first player is a patient who needs quick and accurate medical attention and the second player is the hospital administration that relies on medical experts as well as integrated multi-objective clinical data classification systems for decision-making. The proposed model “MEAF” - Multi-objective Evolutionary Algorithm using Fuzzy Genetics attempts to address accuracy and interpretability simultaneously using Evolutionary Algorithms (EAs). This model enables a $H_{CDSS}$ to detect a disease accurately by using the available resources efficiently. The results of our simulation show that $H_{CDSS}$ produces better and accurate results in detecting disease with efficient resource utilization along with the reduced computational cost. This approach has also produced a better response for both players based on Bayesian Nash Equilibrium. Finally, the proposed model has been tested for accuracy, efficient resource utilization, and computationally cost-effective solution.

[1]  Mingchu Li,et al.  A new prediction model of infectious diseases with vaccination strategies based on evolutionary game theory , 2017 .

[2]  Wei Zhang,et al.  Multi-objective Fuzzy Bi-matrix Game Model: A Multicriteria Non-Linear Programming Approach , 2017, Symmetry.

[3]  Pandian Vasant,et al.  Game-theoretic differential evolution for multiobjective optimization of green sand mould system , 2016, Soft Comput..

[4]  Marian B. Gorzalczany,et al.  Interpretable and accurate medical data classification - a multi-objective genetic-fuzzy optimization approach , 2017, Expert Syst. Appl..

[5]  Marco Archetti,et al.  Cooperation among cancer cells: applying game theory to cancer , 2018, Nature Reviews Cancer.

[6]  Zelda B. Zabinsky,et al.  Using a game-theoretic approach to design optimal health insurance for chronic disease , 2019, IISE Transactions on Healthcare Systems Engineering.

[7]  Mohamed Hamdi,et al.  Game-Based Adaptive Remote Access VPN for IoT: Application to e-Health , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

[8]  John P A Ioannidis,et al.  Modern health care as a game theory problem , 2015, European journal of clinical investigation.

[9]  Jia Hao,et al.  The Research on the Benefit of Telemedicine to Human Based on Evolutionary Game Theory , 2018, HCI.

[10]  Mostafa Ghobaei-Arani,et al.  FAHP approach for autonomic resource provisioning of multitier applications in cloud computing environments , 2018, Softw. Pract. Exp..

[11]  Mohammadreza Ramezanpour,et al.  Mass center direction-based decision method for intraprediction in HEVC standard , 2020, Journal of Real-Time Image Processing.

[12]  Use of Game Theory to model patient engagement after surgery: a qualitative analysis. , 2018, The Journal of surgical research.

[13]  Jun Tanimoto,et al.  A game theoretic approach to discuss the positive secondary effect of vaccination scheme in an infinite and well-mixed population , 2019, Chaos, Solitons & Fractals.

[14]  Jeffrey West,et al.  The Immune Checkpoint Kick Start: Optimization of Neoadjuvant Combination Therapy Using Game Theory. , 2019, JCO clinical cancer informatics.

[15]  Andrzej Bielecki,et al.  Analysis of Healthcare Systems by Using Systemic Approach , 2019, Complex..

[16]  Madjid Tavana,et al.  A hybrid data envelopment analysis and game theory model for performance measurement in healthcare , 2018, Health care management science.

[17]  Alireza Souri,et al.  Multiobjective virtual machine placement mechanisms using nature‐inspired metaheuristic algorithms in cloud environments: A comprehensive review , 2019, Int. J. Commun. Syst..

[18]  P. Pattison,et al.  Game theoretic modelling of infectious disease dynamics and intervention methods: a review , 2019, Journal of biological dynamics.

[19]  C. Corzo,et al.  Individual or Common Good? Voluntary Data Sharing to Inform Disease Surveillance Systems in Food Animals , 2019, Front. Vet. Sci..

[20]  A. Tsourdos,et al.  Multi-objective trajectory optimization of Space Manoeuvre Vehicle using adaptive differential evolution and modified game theory , 2017 .

[21]  Scott A. Huettel,et al.  Bayesian nonparametric models characterize instantaneous strategies in a competitive dynamic game , 2018, bioRxiv.

[22]  Ying-Chang Liang,et al.  A Survey on Applications of Game Theory in Blockchain , 2019, ArXiv.

[23]  Farhad Farokhi A Game-Theoretic Approach to Adversarial Linear Support Vector Classification , 2019, ArXiv.

[24]  Muhammad Fahimullah,et al.  A bi-objective game-theoretic model for collaboration formation between software development firms , 2019, PloS one.

[25]  Alireza Souri,et al.  LP-WSC: a linear programming approach for web service composition in geographically distributed cloud environments , 2018, The Journal of Supercomputing.

[26]  Sohail Asghar,et al.  Using health data repositories for developing clinical system software: a multi-objective fuzzy genetic approach , 2020, IET Softw..

[27]  Amir-Masoud Eftekhari-Moghadam,et al.  Knowledge discovery in medicine: Current issue and future trend , 2014, Expert Syst. Appl..

[28]  Reihaneh Khorsand,et al.  An adaptive scheduling approach based on integrated best-worst and VIKOR for cloud computing , 2020, Comput. Ind. Eng..

[29]  Timothy C. Reluga,et al.  Dynamic and game theory of infectious disease stigmas. , 2019, Journal of theoretical biology.

[30]  Mohammad Sadegh Aslanpour,et al.  CSA-WSC: cuckoo search algorithm for web service composition in cloud environments , 2018, Soft Comput..

[31]  Amir Masoud Rahmani,et al.  A moth‐flame optimization algorithm for web service composition in cloud computing: Simulation and verification , 2018, Softw. Pract. Exp..

[32]  Irina Kareva,et al.  Natural Selection Between Two Games with Applications to Game Theoretical Models of Cancer , 2019, Bulletin of Mathematical Biology.

[33]  Mostafa Ghobaei-Arani,et al.  A self‐learning fuzzy approach for proactive resource provisioning in cloud environment , 2019, Softw. Pract. Exp..