2021/10/12 by Satvik Tripathi, Tripathi, Satvik
Computer Science · Health Professions · Mathematics · Medicine · #Anomaly Detection Techniques and Applications #Artificial Intelligence in Healthcare #COVID-19 diagnosis using AI #COVID-19 epidemiological studies #FOS: Computer and information sciences #Machine Learning (cs.LG) #SARS-CoV-2 and COVID-19 Research
paper · pdf · doi:10.48550/arxiv.2110.09436
openalex publication_date 2021/10/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
With the huge spike in the COVID-19 cases across the globe and reverse\ntranscriptase-polymerase chain reaction (RT-PCR) test remains a key component\nfor rapid and accurate detection of severe acute respiratory syndrome\ncoronavirus 2 (SARS-CoV-2). In recent months there has been an acute shortage\nof medical supplies in developing countries, especially a lack of RT-PCR\ntesting resulting in delayed patient care and high infection rates. We present\na gradient-boosting machine model that predicts the diagnostics result of\nSARS-CoV- 2 in an RT-PCR test by utilizing eight binary features. We used the\npublicly available nationwide dataset released by the Israeli Ministry of\nHealth.\n