机构：[1]The Second Clinical College Guangzhou University of Chinese Medicine Guangzhou, Guangdong, P.R. China[2]Division of Biomedical Statistics and Informatics Mayo Clinic Rochester, MN, USA
As an increasing number of patients seek medical information online, it is crucial to bring expert-vetted information to patients. Multiple expert-vetted online resources exist for their accuracy and authority of medical knowledge. However, it is not clear which resource is better in meeting the information needs of the patients. Utilizing a collection of questions raised by patients with diabetes retrieved from an online forum, we manually evaluated three widely used expert-vetted online resources (WebMD, MedlinePlus, and UpToDate) in terms of content coverage and time spent to find answers. The results indicated that WebMD had slightly better content coverage with less time spent in finding answers. Leveraging the Natural Language Processing (NLP) techniques and a clinical terminology resource, the Unified Medical Language System (UMLS), we demonstrated that WebMD had a higher mapping rate of clinical concepts comparing to other resources.
基金：
Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China [b57004]; China Scholarship Council (CSC)China Scholarship Council
语种：
外文
WOS：
第一作者：
第一作者机构：[1]The Second Clinical College Guangzhou University of Chinese Medicine Guangzhou, Guangdong, P.R. China[2]Division of Biomedical Statistics and Informatics Mayo Clinic Rochester, MN, USA
通讯作者：
推荐引用方式(GB/T 7714)：
Zeng Yuqun,Liu Xusheng,Wang Liwei,et al.Answering Diabetic Patients' Questions Using Expert-vetted Online Resources: A Case Study[J].2016 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM).2016,525-528.doi:10.1109/BIBM.2016.7822575.
APA：
Zeng, Yuqun,Liu, Xusheng,Wang, Liwei,Liu, Hongfang&Wang, Yanshan.(2016).Answering Diabetic Patients' Questions Using Expert-vetted Online Resources: A Case Study.2016 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM),,
MLA：
Zeng, Yuqun,et al."Answering Diabetic Patients' Questions Using Expert-vetted Online Resources: A Case Study".2016 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM) .(2016):525-528
