Research Article
Exploratory Data Analysis of Covid Vaccine Safety Data
@INPROCEEDINGS{10.4108/eai.16-4-2022.2318171, author={Nikhil Gangaramani and Sahil Lotya and Akansha Ahuja and Shivani Kulkarni and Sujata Khedkar and Devesh Rajadhyax}, title={ Exploratory Data Analysis of Covid Vaccine Safety Data}, proceedings={Proceedings of The International Conference on Emerging Trends in Artificial Intelligence and Smart Systems, THEETAS 2022, 16-17 April 2022, Jabalpur, India}, publisher={EAI}, proceedings_a={THEETAS}, year={2022}, month={6}, keywords={adverse drug reaction vaccines topic modeling latent dirichlet allocation named entity recognition pos tagging pharmacovigilance}, doi={10.4108/eai.16-4-2022.2318171} }- Nikhil Gangaramani
Sahil Lotya
Akansha Ahuja
Shivani Kulkarni
Sujata Khedkar
Devesh Rajadhyax
Year: 2022
Exploratory Data Analysis of Covid Vaccine Safety Data
THEETAS
EAI
DOI: 10.4108/eai.16-4-2022.2318171
Abstract
Adverse Drug Reaction (ADR) is a harmful or unpleasant reaction from the use of a medical product. Whenever a vaccine is discovered, it goes through a series of clinical trials. Though these trials are useful to detect ADRs using vaccine safety data, a system to visualize the analysis of the adverse effects of a vaccine considering the patient’s condition would be more helpful to prevent mishaps. To simplify and speed up the process of analysis of ADRs from texts this system implements Exploratory Data Analysis and Natural Language processing techniques wherein the system can generate graphs of analysis of each considered parameter, process textual data for analysis, and also extract medical terms from text using Named Entity Recognition eventually identifying and analyzing potential data of the patient that can lead to an adverse reaction.
