2017
DOI: 10.2196/jmir.7393
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Enhancing Seasonal Influenza Surveillance: Topic Analysis of Widely Used Medicinal Drugs Using Twitter Data

Abstract: BackgroundUptake of medicinal drugs (preventive or treatment) is among the approaches used to control disease outbreaks, and therefore, it is of vital importance to be aware of the counts or frequencies of most commonly used drugs and trending topics about these drugs from consumers for successful implementation of control measures. Traditional survey methods would have accomplished this study, but they are too costly in terms of resources needed, and they are subject to social desirability bias for topics dis… Show more

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Cited by 68 publications
(82 citation statements)
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“…We queried our in-house Twitter adverse drug reaction database first using the original keywords only and then including the variants. 5 The queried dataset consisted of 7.98 million tweets in total with initially unknown numbers of occurrences of each of these terms. Querying using the original keywords retrieved 5579 tweets.…”
Section: Extrinsic Evaluationmentioning
confidence: 99%
“…We queried our in-house Twitter adverse drug reaction database first using the original keywords only and then including the variants. 5 The queried dataset consisted of 7.98 million tweets in total with initially unknown numbers of occurrences of each of these terms. Querying using the original keywords retrieved 5579 tweets.…”
Section: Extrinsic Evaluationmentioning
confidence: 99%
“…Medical concept discovery is the basis of healthcare knowledge discovery strategies such as disease surveillance and adverse drug reaction detection. Healthcare knowledge discovery from social media has been validated as viable in previous works [15,16], and can contribute to the sustainability of public health. Therefore, the adoption of the proposed system can directly or indirectly benefit various participants including health consumers, health service providers, and online healthcare platforms, contributing to the sustainability of the virtualized healthcare industry.…”
Section: Discussionmentioning
confidence: 99%
“…OHCs can also benefit from entity extraction by attracting more participants to engage in the information exchange platforms. Second, medical entity recognition is an essential task in clinical information extraction and medical knowledge discovery [14], and can facilitate a number of healthcare-related applications such as disease surveillance [15] and adverse drug reaction detection [16]. Early detection of disease activity can reduce the impact of certain diseases such as seasonal influenza with a rapid response [17].…”
Section: Introductionmentioning
confidence: 99%
“…[25] to predict number of Influenza-related hospital visits. Others extracted topics from tweets to enhance seasonal Influenza surveillance [26] . The system in Ref.…”
Section: Related Workmentioning
confidence: 99%