Proceedings of The International Conference on Emerging Trends in Artificial Intelligence and Smart Systems, THEETAS 2022, 16-17 April 2022, Jabalpur, India

Research Article

Exploratory Data Analysis of Covid Vaccine Safety Data

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  • @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
Nikhil Gangaramani1, Sahil Lotya1,*, Akansha Ahuja1, Shivani Kulkarni1, Sujata Khedkar2, Devesh Rajadhyax3
  • 1: Computer Engineering, Vivekanand Education Society’s Institute of Technology Mumbai, India
  • 2: Vivekanand Education Society’s Institute of Technology Mumbai, India
  • 3: Cere Labs Pvt. Ltd. Mumbai, India
*Contact email: 2018.sahil.lotya@ves.ac.in

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.