CN109698027A - 一种基于人工神经网络的创伤患者急救智能评估决策方法 - Google Patents

一种基于人工神经网络的创伤患者急救智能评估决策方法 Download PDF

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CN109698027A
CN109698027A CN201811474890.4A CN201811474890A CN109698027A CN 109698027 A CN109698027 A CN 109698027A CN 201811474890 A CN201811474890 A CN 201811474890A CN 109698027 A CN109698027 A CN 109698027A
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姜保国
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Peking University
Peking University Peoples Hospital
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    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
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    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
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Abstract

本发明提供了一种基于人工神经网络的创伤患者急救智能评估决策方法，包括：临床创伤数据库接收创伤数据；对所述临床创伤数据库中的创伤数据进行分析和建模；根据所述分析和建模模块的分析结果提供辅助决策信息；根据所述辅助决策信息确定是否进行手术治疗，并提供手术治疗所需医疗资源信息。本发明能够为创伤治疗提供科学、规范的依据。

Description

一种基于人工神经网络的创伤患者急救智能评估决策方法
技术领域
本发明涉及医疗设备领域，具体涉及一种基于人工神经网络的创伤患者急救智能评估决策方法。
背景技术
创伤是当今世界各国普遍面临的一个重大卫生问题。世界卫生组织报告2000年全球死于创伤的人数约500万，占全球死亡总数的9％。2007年8月中国卫生部发布《中国伤害预防报告》，显示我国每年发生伤害约2亿人次，死亡约70～75万人，占死亡总人数的9%左右，是第5位死亡原因。估算每年因伤害而就医约6200万人次，直接医疗费达650亿元。创伤最容易累及社会劳动力的主体——青壮年人群，由此导致的死亡和残疾对社会经济的影响呈明显上升趋势，给社会、家庭带来沉重的负担。与此同时，创伤患者的救治往往是多学科的联合救治过程，患者伤情重，病情进展快，评估与治疗决策困难，目前没有可靠的评估决策系统辅助医务人员的治疗过程，造成效率低下，人员依赖性强。
另一方面，目前的创伤救治依赖于医生的临床经验，而各地、各个医院的医疗水平和医生的临床经验参差不齐，很难实现科学、规范性的救治。
发明内容
本发明的目的是为创伤的科学、规范救治提供一种信息化决策方法。为实现上述目的，本发明的实施例提供了如下技术方案：
一种基于人工神经网络的创伤患者急救智能评估决策方法，包括：临床创伤数据库接收创伤数据；对所述临床创伤数据库中的创伤数据进行分析和建模；根据所述分析和建模模块的分析结果提供辅助决策信息；根据所述辅助决策信息确定是否进行手术治疗，并提供手术治疗所需医疗资源信息。
作为优选方案，上述方法还包括：将手术治疗结果反馈至所述辅助决策信息。
作为优选方案，上述方法还包括：将临床信息输入所述临床创伤数据库。
作为优选方案，上述方法还包括：对所述分析和建模模块进行修正。
作为优选方案，所述临床创伤数据库由多家医院构建。
本发明的实施例能够辅助医务人员进行创伤治疗，提高效率，降低了对医生的临床经验的依赖性，使得各地、各个医院的医疗水平和医生的临床经验能够得到共同提高，实际上实现了医疗数据、经验、资源的共享，实现科学、规范性的救治。
附图说明
接下来将结合附图对本发明的实施例做进一步详细说明，其中：
图1是采用本发明的实施例的患者急救智能评估决策系统的结构框图。
图2是采用本发明的实施例的患者急救智能评估决策方法的流程图。
具体实施方式
参考图1，本实施例的基于人工神经网络的创伤患者急救智能评估决策系统包括：临床创伤数据库、分析和建模模块、创伤救治辅助决策系统、临床决策支持模块、医生自学习接口和专家修正接口。
临床创伤数据库由一家或者多家医院构建形成，并不断接收新的临床创伤数据。
分析和建模模块用于对临床创伤数据库中的创伤数据进行分析和建模，该分析和建模能够通过例如人工神经元网络实现不断的自学习从而得以完善。作为优选方案，该分析和建模过程能够通过专家修正接口得到建立、干预和修正。
创伤救治辅助决策系统用于根据分析和建模模块的分析结果提供辅助决策信息。临床决策支持模块，用于根据辅助决策信息确定是否进行手术治疗，并提供手术治疗所需医疗资源信息。
医生自学习接口用于将手术治疗结果输入到创伤救治辅助决策系统以实现临床反馈。医生自学习接口还允许医生将临床信息输入临床创伤数据库，以不断丰富数据信息。医生自学习接口为一个或者多个，优选为多个并且设立在不同的医院中。
专家修正接口允许临床专家输入信息从而对所述分析和建模模块进行修正。专家修正接口为一个或者多个，优选为多个并且设立在不同的医院中。
参考图2，该图表明了利用图1中的系统实现的患者急救智能评估决策方法。该方法包括：临床创伤数据库接收创伤数据；对所述临床创伤数据库中的创伤数据进行分析和建模；根据所述分析和建模模块的分析结果提供辅助决策信息；根据所述辅助决策信息确定是否进行手术治疗，并提供手术治疗所需医疗资源信息。
作为优选方案，上述方法还包括：将手术治疗结果反馈至所述辅助决策信息，该操作可由医生完成，从而实现临床反馈。
作为优选方案，上述方法还包括：将临床信息输入所述临床创伤数据库，该操作也可由医生自学习接口完成，从而实现数据录入，更新数据库。
作为优选方案，上述方法还包括：对所述分析和建模模块进行修正，该操作可由临床专家修正接口完成。
作为优选方案，所述临床创伤数据库由多家医院构建。
本实施例中的患者急救智能评估决策系统能够辅助医务人员进行创伤治疗，提高效率，降低了对医生的临床经验的依赖性，使得各地、各个医院的医疗水平和医生的临床经验能够得到共同提高，实际上实现了医疗数据、经验、资源的共享，实现科学、规范性的救治。
以上描述仅为本发明的较佳实施例，并非用来限定本发明实施的范围，对上述实施例所做的等效替换与修饰，均应落于本发明的权利要求保护范围内。

Claims (5)

1.一种基于人工神经网络的创伤患者急救智能评估决策方法，其特征在于，包括：
临床创伤数据库接收创伤数据；
对所述临床创伤数据库中的创伤数据进行分析和建模；
根据所述分析和建模模块的分析结果提供辅助决策信息；
根据所述辅助决策信息确定是否进行手术治疗，并提供手术治疗所需医疗资源信息。
2.根据权利要求1所述的创伤患者急救智能评估决策方法，其特征在于，还包括：将手术治疗结果反馈至所述辅助决策信息。
3.根据权利要求2所述的创伤患者急救智能评估决策方法，其特征在于，还包括：将患者信息输入所述临床创伤数据库。
4.根据权利要求1所述的创伤患者急救智能评估决策方法，其特征在于，还包括：对所述分析和建模模块进行修正。
5.根据权利要求1所述的创伤患者急救智能评估决策方法，其特征在于，所述临床创伤数据库由多家医院构建。
CN201811474890.4A 2018-12-04 2018-12-04 一种基于人工神经网络的创伤患者急救智能评估决策方法 Pending CN109698027A (zh)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050215889A1 (en) * 2004-03-29 2005-09-29 The Board of Supervisory of Louisiana State University Methods for using pet measured metabolism to determine cognitive impairment
CN105023073A (zh) * 2014-04-16 2015-11-04 北京百和园科技有限公司 一种基于人工神经网络的医院智能评估分诊系统
CN107785075A (zh) * 2017-11-01 2018-03-09 杭州依图医疗技术有限公司 基于文本病历的小儿发热疾病深度学习辅助诊断系统

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050215889A1 (en) * 2004-03-29 2005-09-29 The Board of Supervisory of Louisiana State University Methods for using pet measured metabolism to determine cognitive impairment
CN105023073A (zh) * 2014-04-16 2015-11-04 北京百和园科技有限公司 一种基于人工神经网络的医院智能评估分诊系统
CN107785075A (zh) * 2017-11-01 2018-03-09 杭州依图医疗技术有限公司 基于文本病历的小儿发热疾病深度学习辅助诊断系统

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Application publication date: 20190430