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Unfortunately, most of this information is inaccurate or unreliable, making it difficult for regular users to discern reliable sources of information. To determine online source reliability, specific knowledge and domain expertise are necessary. Researchers in health informatics studied a number of linguistic and non-linguistic indicators to assist ordinary individuals in judging medical web page credibility. This study proposes a method that automates the process of assessing the reliability of online medical sites based on textual and non-textual characteristics. To evaluate the proposed approach, we developed a real-world dataset of Arabic web pages that provide medical information. This dataset is the first Arabic medical web page dataset for content credibility evaluation. The hybrid approach was assessed using multiple machine learning and deep learning algorithms on the dataset, providing an accuracy and F1-score of 79 % and 77 %, respectively. We also identify the most observable patterns that help evaluate or detect unreliable web pages written in Arabic. <\/jats:p>","DOI":"10.1177\/14604582211070998","type":"journal-article","created":{"date-parts":[[2022,1,21]],"date-time":"2022-01-21T03:54:02Z","timestamp":1642737242000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["Hybrid machine learning approach for Arabic medical web page credibility assessment"],"prefix":"10.1177","volume":"28","author":[{"given":"Amal","family":"Alasmari","sequence":"first","affiliation":[{"name":"Computer Science Department, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9727-0178","authenticated-orcid":false,"given":"Areej","family":"Alhothali","sequence":"additional","affiliation":[{"name":"Computer Science Department, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia"}]},{"given":"Arwa","family":"Allinjawi","sequence":"additional","affiliation":[{"name":"Computer Science Department, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia"}]}],"member":"179","published-online":{"date-parts":[[2022,1,20]]},"reference":[{"key":"bibr1-14604582211070998","doi-asserted-by":"publisher","DOI":"10.1016\/j.eujim.2018.11.002"},{"key":"bibr2-14604582211070998","doi-asserted-by":"publisher","DOI":"10.1109\/AINA.2012.41"},{"key":"bibr3-14604582211070998","doi-asserted-by":"publisher","DOI":"10.1145\/302979.303001"},{"key":"bibr4-14604582211070998","doi-asserted-by":"publisher","DOI":"10.1145\/301353.301402"},{"key":"bibr5-14604582211070998","doi-asserted-by":"publisher","DOI":"10.1086\/266350"},{"key":"bibr6-14604582211070998","doi-asserted-by":"publisher","DOI":"10.1177\/107769900007700304"},{"key":"bibr7-14604582211070998","volume-title":"Your partner for digital health solutions TU","year":"2015"},{"key":"bibr8-14604582211070998","volume-title":"The social life of health information, 2011","author":"Fox S","year":"2011"},{"key":"bibr9-14604582211070998","doi-asserted-by":"publisher","DOI":"10.1080\/23311886.2017.1302785"},{"key":"bibr10-14604582211070998","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-36973-5_47"},{"key":"bibr11-14604582211070998","doi-asserted-by":"publisher","DOI":"10.1145\/2567948.2579000"},{"key":"bibr12-14604582211070998","volume-title":"Support vector machines","author":"Steinwart I","year":"2008"},{"key":"bibr13-14604582211070998","doi-asserted-by":"publisher","DOI":"10.1080\/10447318.2013.839899"},{"issue":"2","key":"bibr14-14604582211070998","first-page":"15","volume":"16","author":"Zha W","year":"2014","journal-title":"Am Commun J"},{"key":"bibr15-14604582211070998","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2014.11.001"},{"key":"bibr16-14604582211070998","unstructured":"Feng VW, Hirst G. 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Neural network architecture for credibility assessment of textual claims. arXiv preprint arXiv:180310547 2018."},{"key":"bibr19-14604582211070998","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2017.04.003"},{"key":"bibr20-14604582211070998","doi-asserted-by":"publisher","DOI":"10.1145\/3041021.3055133"},{"key":"bibr21-14604582211070998","doi-asserted-by":"publisher","DOI":"10.1145\/2983323.2983661"},{"key":"bibr22-14604582211070998","volume-title":"Hon code certification","year":"2021"},{"key":"bibr23-14604582211070998","volume-title":"Ahrq-agency for healthcare research and quality","author":"AHRQ Organization","year":"2021"},{"key":"bibr24-14604582211070998","doi-asserted-by":"publisher","DOI":"10.1136\/jech.53.2.105"},{"key":"bibr25-14604582211070998","unstructured":"Discern Group Inc. The discern instrument. http:\/\/www.discern.org.uk\/discern_instrument.php, 2021. 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