English

Early Diagnostic Prediction of Covid-19 using Gradient-Boosting Machine Model

Machine Learning 2021-10-20 v2

Abstract

With the huge spike in the COVID-19 cases across the globe and reverse transcriptase-polymerase chain reaction (RT-PCR) test remains a key component for rapid and accurate detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In recent months there has been an acute shortage of medical supplies in developing countries, especially a lack of RT-PCR testing resulting in delayed patient care and high infection rates. We present a gradient-boosting machine model that predicts the diagnostics result of SARS-CoV- 2 in an RT-PCR test by utilizing eight binary features. We used the publicly available nationwide dataset released by the Israeli Ministry of Health.

Keywords

Cite

@article{arxiv.2110.09436,
  title  = {Early Diagnostic Prediction of Covid-19 using Gradient-Boosting Machine Model},
  author = {Satvik Tripathi},
  journal= {arXiv preprint arXiv:2110.09436},
  year   = {2021}
}

Comments

Presented at the Drexel Society of Artificial Intelligence Research Conference, 2021 (arXiv:2110.05263)

R2 v1 2026-06-24T06:58:56.612Z