Detecting Adverse Drug Reaction (ADR) Mentions from Social Media
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Asst. Professor, Department of Information Technology, SRMIST, Kattankulathur
Publication date: 2019-03-16
Eurasian J Anal Chem 2019;14(1):emEJAC191019
Adverse Drug Reaction (ADR) can be described as undesired consequences resulting from consumption of medical prescribed drugs. Such reactions are often missed in clinical trials and are experienced by real world patients. If reported and corrected at early stages, it could be beneficial for other patients having the same disease. Many government agencies across different countries are aiming to collect the real time drug reactions from patients through surveys, reporting tools etc. The direct feedback from patients based on their experience is more relevant and informative in making decisions on restricting adverse drug reactions. This self-reported patient feedback in free flowing format is available from discussions in social media and medical blogs. Such data have more impact than government induced feedback, reporting and surveys. In this paper our primary focus is to utilize social media to mine the ADR mentions from patients. We filter tweets that might have adverse drug reaction mentions. We compare the performance of various classification algorithms in classifying accurately if a tweet comprises of ADR mention or not.