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2022 International Conference on Data Science, Agents and Artificial Intelligence, ICDSAAI 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2259998


Due to pandemic vaccines are developed at a rapid pace. There is a requirement to ensure proper post-market pharmacovigilance. The proposed model will help speed up this process by classifying the Adverse Drug Reactions (ADRs) of the vaccines based on the severity. This will help vaccine manufacturers take necessary and timely action. The model will input the patient data (such as symptoms, vaccination details, and patient health details), which will be preprocessed and cleaned. The ADR will then be classified as a minor, major, or deadly reaction. The system made use of Count Vectors (CV), Word TF-IDF, N-gram TFIDF, and Character TF-IDF feature with Naive Bayes, Random Forest, Logistic Regression, Gradient Boost, and Adaboost machine learning classifiers. Using Random Forest with word-level TF-IDF comparatively a higher accuracy of 93.83% and an F1 score of 0.92 was achieved. © 2022 IEEE.

European Journal of Molecular and Clinical Medicine ; 9(7):6469-6474, 2022.
Article in English | EMBASE | ID: covidwho-2169504


On 11th march 2020, The World Health Organisation had declared COVID- 19 as a Pandemic. The virus engulfed the entire world causing disease ranging from no to minimal symptoms to full blown respiratory and multiorgan systemic infection. Many deaths were reported due to COVID 19 infection. The autopsy on COVID 19 deceased could be useful to add more information about pathophysiology in different vital organs during the course of COVID 19 infection. The present study reports a series of autopsy findings conducted upon the deceased which were either diagnosed COVID-19 positive before death by rapid antigen test and RT-PCR or which turned out to be incidentally positive after death while conducting rapid antigen test before commencement of autopsy. The gross and histopathological examination findings were discussed in the present study. Copyright © 2022 Ubiquity Press. All rights reserved.