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- W3137805612 abstract "Adverse Drug Events (ADE) are negative medical conditions occurring when a drug is used. Social media contains millions of unsolicited and uncensored discussions about medication. Utilizing the health-related social media data for mining drug usage patterns and ADE is the main objective of work reported in this paper. The reviews given by users in social health blogs and forums are collected, preprocessed, and detected for drug names and attributes using named entity recognition methods. Then adverse events are extracted using medical lexicons. Drugs and associated ADEs are extracted using Apriori technique and classified using random forest classifier. The overall ADE detection and extraction are evaluated for its accuracy using traditional IR metrics." @default.
- W3137805612 created "2021-03-29" @default.
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- W3137805612 date "2021-01-01" @default.
- W3137805612 modified "2023-09-25" @default.
- W3137805612 title "Identification of Adverse Drug Events from Social Networks" @default.
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- W3137805612 doi "https://doi.org/10.1007/978-981-16-0167-5_10" @default.
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