Publication: Prediction of pediatric injury by bayesian approach: A proposed framework for pre-diagnosis by automate system
Issued Date
2011-09-29
Resource Type
Other identifier(s)
2-s2.0-80053155620
Rights
Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
Proceedings of the 2011 IEEE International Conference on Information Reuse and Integration, IRI 2011. (2011), 504-506
Suggested Citation
Sakda Arj-Ong, Poonphon Suesaowaluk Prediction of pediatric injury by bayesian approach: A proposed framework for pre-diagnosis by automate system. Proceedings of the 2011 IEEE International Conference on Information Reuse and Integration, IRI 2011. (2011), 504-506. doi:10.1109/IRI.2011.6009606 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/11772
Research Projects
Organizational Units
Authors
Journal Issue
Thesis
Title
Prediction of pediatric injury by bayesian approach: A proposed framework for pre-diagnosis by automate system
Author(s)
Other Contributor(s)
Abstract
World Health Organization categorizes health care into three levels, aiming for an efficiency level of care to patients. Many hospitals in the developing and underdeveloped countries may possess the problems of low efficient medical equipment and not having well-trained medical personnel. This research, software system with Bayesian's approach, is introduced to assist the doctors in evaluating a level of care for injured patients at trauma care center. The cause and effect reasoning with the standard condition of emergency organ system prioritization have been used as the factors. Moreover, their associated probabilities are defined for evaluation. Then a suitable level of care for the treatment is decided automatically. After implementation, consistent decision-making between the system and the expert doctors has been demonstrated with high positive predictive value, negation predictive value, and Likelihood ratio. Furthermore, the subsystem also extends to a joint evaluation, and suggestion can support and guide managerial equipment utilization. © 2011 IEEE.