ارزیابی قابلیت اطمینان روابط بیماری-سؤال در فرم های سلامت آنلاین
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ارزیابی قابلیت اطمینان روابط بیماری-سؤال در فرم های سلامت آنلاین

عنوان فارسی مقاله: ارزیابی قابلیت اطمینان روابط بیماری-سؤال در فرم های سلامت آنلاین: رویکرد پیش بینی پیوند
عنوان انگلیسی مقاله: Evaluating reliability of question-disease relations in online health forms: A link prediction approach
مجله/کنفرانس: پردازش خودکار اطلاعات و انفورماتیک
رشته های تحصیلی مرتبط: پزشکی، مهندسی فناوری اطلاعات
گرایش های تحصیلی مرتبط: انفورماتیک پزشکی
کلمات کلیدی فارسی: انجمن های سلامت آنلاین، روابط بیماری-پرسش، پیش بینی لینک، تجزیه و تحلیل شبکه های اجتماعی
کلمات کلیدی انگلیسی: Online health forums، Question-disease relations، Link prediction، Social network analysis
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: Scopus - Master Journal List - JCR
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.tele.2018.05.009
دانشگاه: Department of Electronics and Automation - Fırat University - Elazığ - Turkey
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2018
ایمپکت فاکتور: 3/788 در سال 2017
شاخص H_index: 42 در سال 2019
شاخص SJR: 1/299 در سال 2017
شناسه ISSN: 0736-5853
شاخص Quartile (چارک): Q1 در سال 2017
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 10
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
کد محصول: E10840
فهرست انگلیسی مطالب

Abstract


Keywords


1- Introduction


2- Link Prediction in Bipartite Networks


3- Intensive link Predictıon (ilp) method


4- Experimental results


5- Reliability of online health forums


6- Conclusion


References

نمونه متن انگلیسی مقاله

Abstract


The Internet has become an indispensable part of human life in today. People can now easily find answers to questions they are curious about via the internet. The short, effortless and free way that the Internet provides is extremely attractive for people to have an idea in subjects they wonder related to their health. There are many online health forums where people can ask questions answered by health professionals. Every day, people ask thousands of questions on these sites and get answers about which diseases their complaints may be related to. The frequent use of online forum sites by people has led to the selection of these forums as data source for this study, and analysis of reliability. Firstly, in this study, link prediction in bipartite social networks, where intensive works have been done and it is applied on many areas nowadays, is tried to be carried out on question-disease bipartite network constructed with data obtained from analysis of online health forums whose use rate increase substantially. For this purpose, a novel link prediction method called as intensive link prediction is proposed, and prediction success of this method is compared with five of similarity-based link prediction methods. Better results have been obtained with the proposed method than the other methods. Then, the accuracy of the answers given to the users on online health forums which received intense interest are tested. The reliability of online health forums is measured by the accuracy analysis performed.


Introduction


Nowadays, the Internet is commonly used in the field of health as it is in every area. People can now easily find answers to questions they are curious about via the Internet. The Internet, through the short, effortless and free way it provides, has become a reference source for people to have ideas about their health problems. People use the Internet for many purposes in health care. They actively employ it to obtain an idea about which disease may be associated with their symptoms when people have certain disease symptoms. There are many online health forum sites where patients and doctors communicate on the Internet. Before people go to the doctor and do some tests, they write their complaints on online forum sites and get information from health professionals. Because of this tendency, forum sites have thousands of questions and answers. The frequent use of online health forums by people has led to the selection of these forums as data source for this study, and analysis of reliability. We live together with many complex systems in our environment. The Internet, nervous system, protein networks, transport networks are some examples of complex networks we encounter. Complex networks are a structure used to model the complex systems, in which links are relationships, and nodes are persons, objects, etc. Complex networks make it easy to analyze the structure of complex systems, their development, and the relationships between the entities they represent. Therefore, the analysis of complex networks has become an important research area in many sciences.

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