论文标题
泻药：可信赖的可解释的Twitter分析模型，用于创伤后应激障碍评估
LAXARY: A Trustworthy Explainable Twitter Analysis Model for Post-Traumatic Stress Disorder Assessment
论文作者
论文摘要
资深心理健康是一个重大的民族问题，因为大量退伍军人从最近在伊拉克战争中返回，并在阿富汗持续军事存在。尽管现有的重要作品已经研究了使用黑盒机器学习技术评估基于Twitter的邮政创伤后应激障碍（PTSD）评估，但由于缺乏临床解释性，临床医生无法信任这些框架。为了获得临床医生的信任，我们探讨了一个大问题，Twitter帖子是否可以提供足够的信息来填补临床PTSD评估调查，这些调查传统上一直信任临床医生？为了回答上述问题，我们提出了泻药（基于语言分析的外部探究）模型，这是一种可解释的人工智能（XAI）模型，用于检测和代表使用修改的语言探究和单词计数（LIWC）分析的Twitter用户的PTSD评估。首先，我们采用经过临床验证的调查工具来从真实的Twitter用户那里收集PTSD评估数据，并使用PTSD评估调查结果开发PTSD语言词典。然后，我们使用PTSD语言词典以及机器学习模型来填充调查工具，以检测PTSD状态及其相应Twitter用户的强度。我们对210个经过临床验证的退伍军人Twitter用户的实验评估提供了PTSD分类及其强度估计的有希望的精确度。我们还评估了我们开发的PTSD语言词典的可靠性和有效性。
Veteran mental health is a significant national problem as large number of veterans are returning from the recent war in Iraq and continued military presence in Afghanistan. While significant existing works have investigated twitter posts-based Post Traumatic Stress Disorder (PTSD) assessment using blackbox machine learning techniques, these frameworks cannot be trusted by the clinicians due to the lack of clinical explainability. To obtain the trust of clinicians, we explore the big question, can twitter posts provide enough information to fill up clinical PTSD assessment surveys that have been traditionally trusted by clinicians? To answer the above question, we propose, LAXARY (Linguistic Analysis-based Exaplainable Inquiry) model, a novel Explainable Artificial Intelligent (XAI) model to detect and represent PTSD assessment of twitter users using a modified Linguistic Inquiry and Word Count (LIWC) analysis. First, we employ clinically validated survey tools for collecting clinical PTSD assessment data from real twitter users and develop a PTSD Linguistic Dictionary using the PTSD assessment survey results. Then, we use the PTSD Linguistic Dictionary along with machine learning model to fill up the survey tools towards detecting PTSD status and its intensity of corresponding twitter users. Our experimental evaluation on 210 clinically validated veteran twitter users provides promising accuracies of both PTSD classification and its intensity estimation. We also evaluate our developed PTSD Linguistic Dictionary's reliability and validity.
