ACM-Automatic Assessment-rev.pdf (455.69 kB)
Using machine learning for automatic identification of evidence-based health information on the web
conference contribution
posted on 2023-06-09, 06:35 authored by Majed M Al-Jefri, Roger Evans, Pietro Ghezzi, Gulden UchyigitAutomatic assessment of the quality of online health information is a need especially with the massive growth of online content. In this paper, we present an approach to assessing the quality of health webpages based on their content rather than on purely technical features, by applying machine learning techniques to the automatic identification of evidence-based health information. Several machine learning approaches were applied to learn classifiers using different combinations of features. Three datasets were used in this study for three different diseases, namely shingles, flu and migraine. The results obtained using the classifiers were promising in terms of precision and recall especially with diseases with few different pathogenic mechanisms.
History
Publication status
- Published
File Version
- Accepted version
Journal
Conference Proceedings of the 2017 International Conference on Digital Health; London, UK; 2-5 July 2017Publisher
Association for Computing MachineryExternal DOI
Page range
167-174ISBN
9781450352499Department affiliated with
- Clinical and Experimental Medicine Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2017-06-08First Open Access (FOA) Date
2017-07-07First Compliant Deposit (FCD) Date
2017-06-08Usage metrics
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