Recently,Jayabalan et al published an important study.The authors defined the liver outcome score as a novel biomarker for predicting liver-related mortality in patients with autoimmune hepatitis-primary biliary chola...Recently,Jayabalan et al published an important study.The authors defined the liver outcome score as a novel biomarker for predicting liver-related mortality in patients with autoimmune hepatitis-primary biliary cholangitis overlap syndrome.After thoroughly reviewing their work,we offer insights that primarily relate to their study design to enhance the medical community’s understanding of this complex disease.展开更多
为了辅助决策者及时有效应对突发事件,降低突发事件带来的各项损失,并解决实时、准确、量化的非精确决策数据客观智能获取问题,从人口基数强大的网络在线评论中提取有价值的情报信息,获得表征为概率语言术语集的决策数据,并提出了一种...为了辅助决策者及时有效应对突发事件,降低突发事件带来的各项损失,并解决实时、准确、量化的非精确决策数据客观智能获取问题,从人口基数强大的网络在线评论中提取有价值的情报信息,获得表征为概率语言术语集的决策数据,并提出了一种基于概率语言术语集和机器学习的突发事件应急决策方法。首先,利用Python编程获取在线评论信息,将获得的信息进行清洗、去重等预处理操作,利用中文自然语言处理(Snow Natural Language Processing, SnowNLP)库对评论进行情感分类,根据情感分类分析结果对评论信息进行统计,从而得到表征为概率语言术语集的各方案在不同属性下的决策属性值;然后,提出基于信息熵和最大化偏差方法的综合权重计算方法,使得属性权重的确定较为客观全面;接着,利用投影法对备选方案进行排序和择优;最后,利用一个实际台风灾害应急决策案例,验证所提方法的可行性和实践性,并通过对比分析与灵敏度分析,验证所提方法的合理性和稳定性。所提方法能够对突发事件网络舆情进行实时监测,可以客观智能获取应急情报数据,并实现对突发事件的有效应对。展开更多
基金Supported by The Key Research and Development Project of the Science and Technology Department of Sichuan Province,China,No.2023YFS0280The High-Level Research Initiation Fund of The First Affiliated Hospital of Chengdu Medical College,China,No.CYFY-GQ43.
文摘Recently,Jayabalan et al published an important study.The authors defined the liver outcome score as a novel biomarker for predicting liver-related mortality in patients with autoimmune hepatitis-primary biliary cholangitis overlap syndrome.After thoroughly reviewing their work,we offer insights that primarily relate to their study design to enhance the medical community’s understanding of this complex disease.
文摘为了辅助决策者及时有效应对突发事件,降低突发事件带来的各项损失,并解决实时、准确、量化的非精确决策数据客观智能获取问题,从人口基数强大的网络在线评论中提取有价值的情报信息,获得表征为概率语言术语集的决策数据,并提出了一种基于概率语言术语集和机器学习的突发事件应急决策方法。首先,利用Python编程获取在线评论信息,将获得的信息进行清洗、去重等预处理操作,利用中文自然语言处理(Snow Natural Language Processing, SnowNLP)库对评论进行情感分类,根据情感分类分析结果对评论信息进行统计,从而得到表征为概率语言术语集的各方案在不同属性下的决策属性值;然后,提出基于信息熵和最大化偏差方法的综合权重计算方法,使得属性权重的确定较为客观全面;接着,利用投影法对备选方案进行排序和择优;最后,利用一个实际台风灾害应急决策案例,验证所提方法的可行性和实践性,并通过对比分析与灵敏度分析,验证所提方法的合理性和稳定性。所提方法能够对突发事件网络舆情进行实时监测,可以客观智能获取应急情报数据,并实现对突发事件的有效应对。
