%0期刊文章%@ 1438- 8871% I JMIR出版物%V 24卡塔尔世界杯8强波胆分析% N 8% P e30634 %T识别在线健康社区患者决策过程中的影响:数据科学方法%李a，史明达，陈锦和%陈a,Yi %+马丁塔奇曼管理学院，新泽西理工学院，184-198中央大道，纽瓦克，新泽西州，07102，美国，1 973 596 6302,yi.chen@njit.edu %K影响关系%K决策线程%K在线健康社区%K患者参与%K深度学习%K文本相关性测量%D 2022 %7 31.8.2022 %9原创论文%J J医学互联网Res %G英文%X背景:近年来，越来越多的用户加入在线卫生社区以获取信息和寻求支持。患者经常寻求信息和建议，以支持他们的医疗保健决策。重要的是要了解患者的决策过程，并确定患者从OHCs中获得的影响。目的:我们旨在确定讨论线程中对寻求决策帮助的用户有影响的帖子。方法:提出讨论区帖子影响关系的定义。然后，我们开发了一个框架和深度学习模型来识别影响关系。我们利用最先进的文本相关性测量方法来生成稀疏特征向量来表示文本相关性。我们将一个帖子中问题和动作出现的概率建模为密集特征。 We then used deep learning techniques to combine the sparse and dense features to learn the influence relationships. Results: We evaluated the proposed techniques on discussion threads from a popular cancer survivor OHC. The empirical evaluation demonstrated the effectiveness of our approach. Conclusions: It is feasible to identify influence relationships in OHCs. Using the proposed techniques, a significant number of discussions on an OHC were identified to have had influence. Such discussions are more likely to affect user decision-making processes and engage users’ participation in OHCs. Studies on those discussions can help improve information quality, user engagement, and user experience. %M 36044266 %R 10.2196/30634 %U //www.mybigtv.com/2022/8/e30634 %U https://doi.org/10.2196/30634 %U http://www.ncbi.nlm.nih.gov/pubmed/36044266