Personalized predictions of adverse side effects of the COVID-19 vaccines.

ABSTRACT:

Background

Misconceptions about adverse side effects are thought to influence public acceptance of the Coronavirus disease 2019 (COVID-19) vaccines negatively. To address such perceived disadvantages of vaccines, a novel machine learning (ML) approach was designed to generate personalized predictions of the most common adverse side effects following injection of six different COVID-19 vaccines based on personal and health-related characteristics.

Methods

Prospective data of adverse side effects following COVID-19 vaccination in 19943 participants from Iran and Switzerland was utilized. Six vaccines were studied: The AZD1222, Sputnik V, BBIBP-CorV, COVAXIN, BNT162b2, and the mRNA-1273 vaccine. The eight side effects were considered as the model output: fever, fatigue, headach

SUBMITTER: Jamshidi E 

PROVIDER: S-EPMC9800018 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature