基于深度学习的医院财务分析系统的设计与研究  

Design and research of hospital financial analysis system based on deep learning

作　　者：陈树斐 吴洋 CHEN Shufei;WU Yang(The First Affiliated Hospital of Hebei North University,Zhangjiakou 075000,China)

机构地区：[1]河北北方学院附属第一医院,河北张家口075000

出　　处：《电子设计工程》2025年第5期31-34,39,共5页Electronic Design Engineering

摘　　要：为提升医院财务管理效率和决策准确性,设计了一种基于深度学习技术的医院财务分析系统。通过分析医院财务数据,利用长短期记忆(LSTM)网络和门控循环单元(GRU)等深度学习模型进行收入预测和成本控制,并采用聚类分析、关联规则挖掘等方法,识别潜在财务风险。结果表明,所设计的医院财务分析系统在预测准确性和风险识别方面表现出色,显著优于传统方法。基于深度学习技术的医院财务分析系统能够显著改善医院财务管理情况,为其提供了有效的决策支持。In order to improve the efficiency of hospital financial management and decision accuracy,a hospital financial analysis system based on deep learning technology is designed.Through the analysis of hospital financial data,deep learning models such as Long-and Short-Term Memory(LSTM)network and Gating Recurrent Unit(GRU)are used to conduct revenue prediction and cost control,and cluster analysis and association rule mining are used to identify potential financial risks.The results showed that the designed hospital financial analysis system performed well in prediction accuracy and risk identification and significantly outperformed the traditional methods.The hospital financial analysis system based on deep learning technology can significantly improve the hospital financial management and provide effective decision support.

关 键 词：医院财务管理 深度学习 预测 风险识别 

分 类 号：TN919[电子电信—通信与信息系统]