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实现灾难应急医学救援数据资源智能化管理的思考
引用本文:沈洪,刘中民. 实现灾难应急医学救援数据资源智能化管理的思考[J]. 同济大学学报(医学版), 2018, 39(5): 1-4
作者姓名:沈洪  刘中民
作者单位:中国人民解放军总医院,北京100853,同济大学附属东方医院,上海200120
摘    要:科学应对灾难救援已成为全球关注的热点和当今社会的普遍共识。人工智能技术有助于人类未来预防灾难、抵御灾难,可最大限度地减少灾难损失的影响,是最具前景的发展领域。目前,中国政府从科技研发、应用推广和产业发展等层面提出了一系列措施,也为智能化灾难应急医学救援的发展指出了方向。通过灾难数据信息智能化管理可优化整合各种资源,减少不必要浪费,也能获得更好的综合判断结论和更合理的应对决策。采用智能大数据技术与灾难救援产业结合作为创新研发突破点,并应用于灾难救援实践中,可以大幅度提升我国灾害应急救援水平。结合灾难前、灾难中、灾难后的复杂性、特殊性的实情,积极开拓灾难预防应急智能技术,使之成为有助公众防灾避险的智能工具。

关 键 词:灾难; 应急救援; 灾难医学; 人工智能; 数据资源; 智能化管理
收稿时间:2018-07-04

Intelligent management of data source in disaster medical emergency rescue
SHEN Hong and LIU Zhong-min. Intelligent management of data source in disaster medical emergency rescue[J]. Journal of Tongji University(Medical Science), 2018, 39(5): 1-4
Authors:SHEN Hong and LIU Zhong-min
Affiliation:Chinese PLA General Hospital, Beijing 100853, China and East Hospital, Tongji University, Shanghai 200120, China
Abstract:Prompt response to disasters rescue has become the focus of global attention and the consensus of the society. Artificial intelligence(AI) is the most promising development field in preventing and combating disasters, and minimizing the damage of disasters in the future. The government has put forward a series of measures in disaster management: scientific and technological research, application promotion and industrial development, as well as the development of intelligent emergency medical rescue. The intelligent management will optimize and integrate disaster data sources, and avoid unnecessary waste, for better comprehensive judgment and more reasonable decision making. The combination of intelligent big data with disaster rescue industry is a breakthrough point of innovation research and development, and it will greatly improve the disaster emergency rescue in China. The intelligent technology developed on basis of the complex and real situation of disaster, will be a useful tool for the public in disaster prevention and emergency response.
Keywords:disaster   emergency rescue   disaster medicine   artificial intelligence   data resources   intelligent management
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