Artificial Intelligent Manual–Machine Interaction on Integrated Emergency Information System

As an important part of healthcare service in hospitals, the emergency system is the most concentrated and complex department for severe patients. With artificial intelligence, the development of manual–machine interaction system effectively improves the efficiency of medical treatment for avoiding doctors from daily manual operations in emergencies, and it promotes emergency doctors to focus more on patients. The ultimate goal of emergency department information establishment aims to construct a complete clinical process with electronic, standard and optimal directions in emergency. It achieves information sharing and quality control among all steps in the process, and forms a complete solution plan for emergency, including: integration, information and networking of pre-hospital first aid, hospital triage, emergency reception, rescue, emergency observation and monitoring. This paper aims to propose and construct a highly integrated emergency clinical information system and focus on resolving the missing and demanding parts of hospital information chain, and the proposed system is available for standardizing and optimizing the clinical workflow in emergency. It realizes the integration, informatization, networking and mobility of the emergent workflow, and upgrades the efficiency and management level in emergency. For changing the conventional mode in clinics and optimizing the process of emergent treatment, it also develops an application that closely meets the actual demands of emergency department in hospitals. It also provides the statistical inquiry and analysis of daily business and quality indicators to manifest the medical performance and quality management for hospital emergency department in clinics.

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Publication Details

Journal
International Journal of Pattern Recognition and Artificial Intelligence
Published
2025-10-23
DOI
https://doi.org/10.1142/s0218001425500351
Primary Topic
Edcuational Technology Systems
Type
article
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article

Artificial Intelligent Manual–Machine Interaction on Integrated Emergency Information System

Xin Xia, Jianwei Lu, Yunlong Ma, Ye Luo
International Journal of Pattern Recognition and Artificial Intelligence
Edcuational Technology Systems
article

Artificial Intelligent Manual–Machine Interaction on Integrated Emergency Information System

Xin Xia, Jianwei Lu, Yunlong Ma, Ye Luo
article en

Abstract

As an important part of healthcare service in hospitals, the emergency system is the most concentrated and complex department for severe patients. With artificial intelligence, the development of manual–machine interaction system effectively improves the efficiency of medical treatment for avoiding doctors from daily manual operations in emergencies, and it promotes emergency doctors to focus more on patients. The ultimate goal of emergency department information establishment aims to construct a complete clinical process with electronic, standard and optimal directions in emergency. It achieves information sharing and quality control among all steps in the process, and forms a complete solution plan for emergency, including: integration, information and networking of pre-hospital first aid, hospital triage, emergency reception, rescue, emergency observation and monitoring. This paper aims to propose and construct a highly integrated emergency clinical information system and focus on resolving the missing and demanding parts of hospital information chain, and the proposed system is available for standardizing and optimizing the clinical workflow in emergency. It realizes the integration, informatization, networking and mobility of the emergent workflow, and upgrades the efficiency and management level in emergency. For changing the conventional mode in clinics and optimizing the process of emergent treatment, it also develops an application that closely meets the actual demands of emergency department in hospitals. It also provides the statistical inquiry and analysis of daily business and quality indicators to manifest the medical performance and quality management for hospital emergency department in clinics.

International Journal of Pattern Recognition and Artificial IntelligenceVol. 40(04)
Tongji University (CN), Shanghai Innovative Research Center of Traditional Chinese Medicine (CN), Shanghai University of Traditional Chinese Medicine (CN), Shanghai East Hospital (CN)
Openalex Percentile: Top 84%
Edcuational Technology Systems
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