TY -的AU -琼斯,Josette AU -普拉丹,Meeta盟——Hosseini Masoud盟——Kulanthaivel Anand盟——Hosseini Mahmood PY - 2018 DA - 2018/11/29 TI -小说集群方法我们数据转化为可操作的主题:案例研究一个基于web的乳腺癌论坛乔-地中海JMIR通知SP - e45六世- 6 - 4 KW -数据解释KW -自然语言处理KW——我们相信信息KW——社交媒体KW -统计分析KW - infodemiology AB -背景:越来越多地使用社交媒体和移动医疗应用程序，为医疗保健消费者提供了分享自己健康和福祉信息的新机会。通过社交媒体分享的信息不仅包括医疗信息，还包括幸存者在日常生活中如何管理疾病和恢复的宝贵信息。目的:本研究的目的是确定获取一个主要的乳腺癌在线支持论坛的主题和建模的可行性。我们选择了乳腺癌患者支持论坛，以发现疾病管理和康复中隐藏的、不太明显的方面。方法:首先，采用各论坛板块的定性内容分析(QCA)进行人工主题分类。其次，我们请求Breastcancer.org社区允许对这些帖子进行更深入的分析。然后使用开源软件机器学习语言工具包进行主题建模，然后进行多元线性回归(MLR)分析，以检测不同网站论坛之间高度相关的主题。结果:论坛的QCA产生了20个用户讨论类别。最终的主题模型将400万个帖子组织成30个可管理的主题。 Using qualitative analysis of the topic models and statistical analysis, we grouped these 30 topics into 4 distinct clusters with similarity scores of ≥0.80; these clusters were labeled Symptoms & Diagnosis, Treatment, Financial, and Family & Friends. A clinician review confirmed the clinical significance of the topic clusters, allowing for future detection of actionable items within social media postings. To identify the most significant topics across individual forums, MLR demonstrated that 6 topics—based on the Akaike information criterion values ranging from −642.75 to −412.32—were statistically significant. Conclusions: The developed method provides an insight into the areas of interest and concern, including those not ascertainable in the clinic. Such topics included support from lay and professional caregivers and late side effects of therapy that consumers discuss in social media and may be of interest to clinicians. The developed methods and results indicate the potential of social media to inform the clinical workflow with regards to the impact of recovery on daily life. SN - 2291-9694 UR - http://medinform.www.mybigtv.com/2018/4/e45/ UR - https://doi.org/10.2196/medinform.9162 UR - http://www.ncbi.nlm.nih.gov/pubmed/30497991 DO - 10.2196/medinform.9162 ID - info:doi/10.2196/medinform.9162 ER -