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Game-Theory Based Graded Diagnosis Strategies of Craniocerebral Injury

Yiming Liu1, Ke Chen1, Lanzhen Bian2, Lei Ren3, Jing Hu4,*, Jinyue Xia5

1 Department of neurosurgery, Children’s Hospital of Nanjing Medical University, Nanjing, 210008, China
2 Department of surgery, Children’s Hospital of Nanjing Medical University, Nanjing, 210008, China
3 Department of Nursing, Children’s Hospital of Nanjing Medical University, Nanjing, 210008, China
4 Department of rehabilitation medicine, Children’s Hospital of Nanjing Medical University, Nanjing, 210008, China
5 International Business Machines Corporation (IBM), NY, USA

* Corresponding Author: Jing Hu. Email: email

Intelligent Automation & Soft Computing 2021, 30(2), 553-561. https://doi.org/10.32604/iasc.2021.017391

Abstract

Craniocerebral injury is a common surgical emergency in children. It has the highest mortality and disability rate, and the second highest incidence rate. Accidental injuries due to falls, sports and traffic accidents are the main causes of craniocerebral injury. In recent years, the incidence rate of craniocerebral injury in children has continued to rise, which injury stretches out the limited medical resources. Moreover, it is very difficult to deal with complex craniocerebral trauma in the hospital of county town, in which is not rich in medical resources because of the lack of experienced doctors and nurses. In addition, some children with mild craniocerebral injury go to tertiary hospitals directly, which takes up a lot of medical resources and leads to the waste of medical resources. To solve the problem, the Game Model is used to model the graded diagnosis and treatment strategies of craniocerebral injury in this paper. The results show that the diversion of some children who are identified as mild to moderate craniocerebral injury can increase the turnover of hospital beds in a tertiary hospital. Accordingly, the limited medical resources can be used to treat those children who are in critical conditions. In addition, the data also verifies the effectiveness of graded diagnosis and treatment strategies.

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APA Style
Liu, Y., Chen, K., Bian, L., Ren, L., Hu, J. et al. (2021). Game-theory based graded diagnosis strategies of craniocerebral injury. Intelligent Automation & Soft Computing, 30(2), 553-561. https://doi.org/10.32604/iasc.2021.017391
Vancouver Style
Liu Y, Chen K, Bian L, Ren L, Hu J, Xia J. Game-theory based graded diagnosis strategies of craniocerebral injury. Intell Automat Soft Comput . 2021;30(2):553-561 https://doi.org/10.32604/iasc.2021.017391
IEEE Style
Y. Liu, K. Chen, L. Bian, L. Ren, J. Hu, and J. Xia "Game-Theory Based Graded Diagnosis Strategies of Craniocerebral Injury," Intell. Automat. Soft Comput. , vol. 30, no. 2, pp. 553-561. 2021. https://doi.org/10.32604/iasc.2021.017391



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