TY - GEN
T1 - Prediction of pediatric injury by bayesian approach
T2 - 12th IEEE International Conference on Information Reuse and Integration, IRI 2011
AU - Arj-Ong, Sakda
AU - Suesaowaluk, Poonphon
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
KW - Bayesian
KW - Child injury
KW - Decision support system
KW - Injury prediction model
KW - trauma center
UR - https://www.scopus.com/pages/publications/80053155620
U2 - 10.1109/IRI.2011.6009606
DO - 10.1109/IRI.2011.6009606
M3 - Conference contribution
AN - SCOPUS:80053155620
SN - 9781457709661
T3 - Proceedings of the 2011 IEEE International Conference on Information Reuse and Integration, IRI 2011
SP - 504
EP - 506
BT - Proceedings of the 2011 IEEE International Conference on Information Reuse and Integration, IRI 2011
Y2 - 3 August 2011 through 5 August 2011
ER -