Prolonged viral shedding prediction on non-hospitalized, uncomplicated SARS-CoV-2 patients using their transcriptome data.

ABSTRACT: Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is identified as a highly transmissible coronavirus which threatens the world with this deadly pandemic. WHO reported that it spreads through contact, droplet, airborne, formite, fecal-oral, bloodborne, mother-to-child and animal-to-human. Hence, viral shedding has a huge impact on this pandemic. This study uses transcriptome data of coronavirus disease 2019 (COVID-19) patients to predict the prolonged viral shedding of the corresponding patient. This prediction starts with the transcriptome features which gives the lowest root mean squared value of 16.3±3.3 using top 25 feature selected using forward feature selection algorithm and linear regression algorithm. Then to see the impact of few non-molecular features in this pre

SUBMITTER: Jeyananthan P 

PROVIDER: S-EPMC9444307 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature