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Medical Information Mining-Based Visual Artificial Intelligence Emergency Nursing Management System.
Dong, Aihua; Guo, Jian; Cao, Yongzhi.
Afiliación
  • Dong A; Department of Emergency, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China.
  • Guo J; Department of Emergency, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China.
  • Cao Y; Transfusion Center, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China.
J Healthc Eng ; 2021: 4253606, 2021.
Article en En | MEDLINE | ID: mdl-34868517
ABSTRACT
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Enfermería de Urgencia Límite: Humans Idioma: En Revista: J Healthc Eng Año: 2021 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Enfermería de Urgencia Límite: Humans Idioma: En Revista: J Healthc Eng Año: 2021 Tipo del documento: Article País de afiliación: China
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