Penerapan Stacking untuk Optimasi Model Diagnosa Coronavirus Disease 19 (COVID-19)
DOI:
https://doi.org/10.32493/jtsi.v7i2.38936Keywords:
Stacking, Optimization of the Diagnostic Model, COVID-19Abstract
Laboratory test results in COVID-19 patients are not specific, but lymphopenia, increased lactate dehydrogenase and increased aminotransferases are often found. Meanwhile, chest imaging examination can show a picture of pneumonia. Until now, there has been no specific therapy in the treatment of COVID-19. There are two of the largest studies on COVID-19 therapy which are currently still running globally. Studies show that the antiviral favipiravir, remdesivir, and tocilizumab may have some benefits for treating COVID-19, and their use has been approved in Indonesia. There have been many diagnostic methods using machine learning that are used to detect whether someone has COVID-19 or not. However, the accuracy of the test may vary depending on when your sample was taken during the course of your disease. If you get tested too soon after exposure to COVID-19, there may not be enough virus in your body to get an accurate result. If this was the case at the time of the test, your test may come back negative, even if you do have the virus. This will be considered a 'false negative' test. It is important to understand that healthcare professionals consider a number of factors in making a diagnosis of COVID-19. In this study using the experimental method by making applications to implement the proposed algorithm. Then test the model using a secondary dataset downloaded from Kaggle and measure the performance of the model.
References
Burhan, E., Susanto, A. D., Nasution, S. A., Ginanjar, E., Pitoyo, W., Susilo, A., & Dkk. (2020). Pedoman Tatalaksana COVID-19. In Pedoman Tatalaksana COVID-19 (3rd ed.).
Cascella, M., Rajnik, M., Cuomo, A., Dulebohn, S. C., & Napoli, R. Di. (2022). Features, Evaluation, and Treatment of Coronavirus (COVID-19). StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2022 Jan–., December 2020, 1–49.
Cennimo, D. J. (2024). Coronavirus Disease 2019 (COVID-19) (pp. 1–4). Medscape.
Guo, Y.-R., Cao, Q.-D., Hong, Z.-S., Tan, Y.-Y., Chen, S.-D., Jin, H.-J., Tan, K.-S., Wang, D.-Y., & Yan, Y. (2020). The Origin, Transmission and Clinical Therapies on Coronavirus Disease 2019 (COVID-19) Outbreak – An Update on the Status. Military Medical Research, 7(11), 1–10. https://doi.org/10.1186/s40779-020-00240-0
McIntosh, K., Hirsch, M. S., & Bloom, A. (2020). Coronavirus Disease 2019 (COVID-19). UpToDate, 1–27. https://www.cmim.org/PDF_covid/Coronavirus_disease2019_COVID-19_UpToDate2.pdf
Mendez, C. M. (2020). Solidarity” Clinical Trial for COVID -19 Treatments. Brazilian Journal of Impleantology and Health Sciences, 1–6.
Oxford University. (2022). The RECOVERY Trial - two years on (pp. 1–2). Oxford University.
Sahin, A. R., Erdogan, A., Mutlu Agaoglu, P., Dineri, Y., Cakirci, A. Y., Senel, M. E., Okyay, R. A., & Tasdogan, A. M. (2020). 2019 Novel Coronavirus (COVID-19) Outbreak: A Review of the Current Literature. Eurasian Journal of Medicine and Oncology, 4(1), 1–7. https://doi.org/10.14744/ejmo.2020.12220
World Health Organization. (2020). Laboratory Testing for 2019 Novel Coronavirus (2019-nCoV) in Suspected Human Cases. In WHO - Interim guidance (pp. 1–7). World Health Organization. https://www.who.int/publications/i/item/WHO-2019-nCoV-lab-testing-2021.1-eng
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