Saberi Nahid, Mahvash Mohsen, Zenati Marco
Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:218-21. doi: 10.1109/EMBC.2015.7318339.
We introduce an intelligent system to optimize a team composition based on the team's historical outcomes and apply this system to compose a surgical team. The system relies on a record of the procedures performed in the past. The optimal team composition is the one with the lowest probability of unfavorable outcome. We use the theory of probability and the inclusion exclusion principle to model the probability of team outcome for a given composition. A probability value is assigned to each person of database and the probability of a team composition is calculated from them. The model allows to determine the probability of all possible team compositions even if there is no recoded procedure for some team compositions. From an analytical perspective, assembling an optimal team is equivalent to minimizing the overlap of team members who have a recurring tendency to be involved with procedures of unfavorable results. A conceptual example shows the accuracy of the proposed system on obtaining the optimal team.
我们引入了一个智能系统，该系统可根据团队的历史结果来优化团队组成，并将此系统应用于组建手术团队。该系统依赖于过去执行手术的记录。最佳团队组成是产生不良结果概率最低的组合。我们使用概率论和容斥原理对给定组成的团队结果概率进行建模。为数据库中的每个人分配一个概率值，并据此计算团队组成的概率。即使某些团队组成没有记录的手术，该模型也能确定所有可能团队组成的概率。从分析角度来看，组建最佳团队等同于尽量减少那些经常参与产生不良结果手术的团队成员之间的重叠。一个概念性示例展示了所提出系统在获得最佳团队方面的准确性。
