Department of Emergency, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China.
Transfusion Center, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China.
J Healthc Eng. 2021 Nov 25;2021:4253606. doi: 10.1155/2021/4253606. eCollection 2021.
This study aims to design a set of the visual artificial intelligence system based on medical information mining for hospital emergency care management. A visual artificial intelligence emergency first aid nursing management system is designed by analyzing the needs of the emergency first aid nursing management system. The results show that system personnel allocation, comparative management, record management, query management analysis, basic setup analysis, nursing management basis, and nonfunctional requirements all need to be optimized for the emergency first aid management system. In this study, the comparative management module, log management module, and the query management module are designed, and the emergency first aid management system of different APP terminal functions in different modules is described in detail. The nursing document query business is tested, and the corresponding time of query of nursing assessment sheet, nurse shift record, nurse record, and physical sign observation sheet is 375.50 ms, 351.48 ms, 336.36 ms, and 245.57 ms, respectively. It shows that the visual artificial intelligence emergency nursing management system based on medical information mining can provide convenience for clinical work to a large extent and has potential application value in hospital emergency nursing work.
本研究旨在设计一套基于医学信息挖掘的可视化人工智能系统，用于医院急诊护理管理。通过分析急诊护理管理系统的需求，设计了可视化人工智能急诊急救护理管理系统。结果表明，系统人员配置、对比管理、记录管理、查询管理分析、基础设置分析、护理管理基础和非功能需求都需要对急诊急救管理系统进行优化。本研究设计了对比管理模块、日志管理模块和查询管理模块，并详细描述了不同模块中不同 APP 终端功能的急诊急救管理系统。对护理文档查询业务进行了测试，护理评估表、护士交接班记录、护士记录和体征观察表的查询相应时间分别为 375.50ms、351.48ms、336.36ms 和 245.57ms。这表明，基于医学信息挖掘的可视化人工智能急诊护理管理系统可以在很大程度上为临床工作提供便利，在医院急诊护理工作中具有潜在的应用价值。
