基于联邦增量学习的医院财务信息局域共享方法

Local sharing method of hospital financial information based on federated incremental learning

为实现对医院财务信息的更新与共享,提出基于联邦增量学习的信息局域共享方法。首先,由粒子优化算法以寻优的方式,设臵支持向量机参数,基于改进后的支持向量机建立新增财务信息分类模型;然后,基于联邦增量学习设计财务信息更新方法,自动修正更新医院财务信息;最后,基于身份验证过程设计财务信息局域共享方法,用户需以秘密验证的方式验证自身身份,验证通过后才具备财务信息局域共享权限。实验表明:该方法可以有效保证财务数据信息安全性,且财务信息增量更新后,信息之间冗余度仅有0.01。相比于传统方法,该方法的共享时效性较高。

To achieve the update and sharing of hospital financial information,a local information sharing method based on federated incremental learning is proposed.Firstly,the particle optimization algorithm sets support vector machine parameters through optimization,and establishes a new financial information classification model based on the improved support vector machine;Then,based on federated incremental learning,a financial information update method is designed to automatically correct and update hospital financial information;Finally,based on the identity verification process,a financial information local sharing method is designed.Users need to verify their identity through secret verification,and only after passing the verification can they have financial information local sharing permissions.The experiment shows that this method can effectively ensure the security of financial data information,and after the incremental update of financial information,the redundancy between information is only 0.01.Compared to traditional methods,this method has higher sharing timeliness.