智能健康软件为紧急情况下的救援人员提供支持

Abu Shad Ahammed, Roman Obermaisser
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引用次数: 0

摘要

世界各地的救援站每年都会接到数百万个紧急救援电话,其中大部分都是由于健康问题引起的。由于救援服务的高频率和必要性,对救援人员做出快速、准确和协调响应以挽救生命和减少损失的需求一直在不断增加。本文介绍了一种救援健康管理软件解决方案,旨在利用人工智能驱动的决策支持系统快速评估紧急病人的健康状况,从而提高救援态势感知的效率和效果。这种软件方法的新颖之处在于它采用了以用户为中心的设计原则,以确保其解决方案是专门为满足应急响应人员的独特需求而量身定制的。它利用预先训练好的机器学习模型和抢救数据,并接受新病人的输入数据,提供主要健康并发症的可能性,以便抢救人员能根据结果推断治疗方案。本文主要介绍了软件开发和实施步骤以及三个使用案例,同时还简要概述了之前基于机器学习的开发阶段。
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Smart Health Software to Support Rescue Personnel in Emergency Situations
Rescue stations around the world receive millions of emergency rescue calls each year, most of which are due to health complications. Due to the high frequency and necessity of rescue services, there is always an increasing demand for quick, accurate, and coordinated responses from rescue personnel to save lives and mitigate damage. This paper introduces a rescue health management software solution designed to improve the efficiency and effectiveness of rescue situational awareness by rapidly assessing the health status of emergency patients using AI-driven decision support systems. The novelty in this software approach is it's user-centered design principles to ensure that its solutions are specifically tailored to meet the unique requirements of emergency responders. It used pre-trained machine learning models with rescue data and accepted new patient's input data to provide a probability of the major health complications so that rescue personnel can expedite treatment plan following the outcome. The paper focuses primarily on the software development and implementation steps with three use cases, while also providing a short overview of the previous machine learning-based development phases.
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