Machine learning (ML] helps with the future prediction of action and take decision. A variety of prediction techniques are used for the future prediction of risks and effectively dealing it. This work shows how ML models can predict death rates of COVID-19 patients so that we can do effective treatment and try to minimize the effect of the causes. Coronavirus 2019, COVID-19 is a member of the Coronaviridae genus. A virus without a cure causes unpredictable devastation to people's lives as well as the financial and economic systems of every nation on earth. We have taken certain features from the COVID-19 dataset to study and comprehend the future circumstance using machine learning algorithms, various prediction models are created, and their performances are calculated and assessed. We have compared machine learning algorithms viz. Random Forest and Linear Regression, Decision Tree to predict a number of cases.
This work is licensed under a Creative Commons Attribution 4.0 International License.
- Aljameel, S. S., Khan, I. U., Aslam, N., Aljabri, M., and Alsulmi, E. S. 2021. Machine learning-based model to predict the disease severity and outcome in covid-19 patients. Scientific programming 2021. DOI: https://doi.org/10.1155/2021/5587188
- Ardabili, S. F., Mosavi, A., Ghamisi, P., Ferdinand, F., Varkonyi-Koczy, A. R.,Reuter, U., Rabczuk, T., and Atkinson, P. M. 2020. Covid-19 outbreak prediction with machine learning. Algorithms 13, 10, 249. DOI: https://doi.org/10.3390/a13100249
- Ebrahim Abbasi-Oshaghi, Fatemeh Mirzaei, F. F. I. K. and Tayebiniaf, H. 2020. Diagnosis and treatment of coronavirus disease 2019 (covid-19): Laboratory, pcr, and chest ct imaging findings. international journal of surgery (london, england). DOI: https://doi.org/10.1016/j.ijsu.2020.05.018
- Kwekha-Rashid, A. S., Abduljabbar, H. N., and Alhayani, B. 2021. Coronavirus disease (covid-19) cases analysis using machine-learning applications. Applied Nanoscience, 1–13. DOI: https://doi.org/10.1007/s13204-021-01868-7
- Prakash, K. B., Imambi, S. S., Ismail, M., Kumar, T. P., and Pawan, Y. 2020. Analysis,prediction and evaluation of covid-19 datasets using machine learning algorithms. International Journal 8, 5,2199–2204. DOI: https://doi.org/10.30534/ijeter/2020/117852020
- Rustam, F., Reshi, A. A., Mehmood, A., Ullah, S., On, B.-W., Aslam, W., and Choi,G. S. 2020a. Covid-19 future forecasting using supervised machine learning models. IEEE access 8, 101489–101499.
- Rustam, F., Reshi, A. A., Mehmood, A., Ullah, S., On, B.-W., Aslam, W., and Choi,G. S. 2020b. Covid-19 future forecasting using supervised machine learning models. IEEE access 8, 101489–101499. DOI: https://doi.org/10.1109/ACCESS.2020.2997311
- Tuli, S., Tuli, S., Tuli, R., and Gill, S. S. 2020. Predicting the growth and trend of covid-19 pandemic using machine learning and cloud computing. Internet of Things 11, 100222. DOI: https://doi.org/10.1016/j.iot.2020.100222
- Wang, P., Zheng, X., Li, J., and Zhu, B. 2020. Prediction of epidemic trends in covid-19 with logistic model and machine learning technics. Chaos, Solitons & Fractals 139, 110058. DOI: https://doi.org/10.1016/j.chaos.2020.110058
- Zoabi, Y., Deri-Rozov, S., and Shomron, N. 2021. Machine learning-based prediction of covid-19 diagnosis based on symptoms. npj digital medicine 4, 1, 1–5 DOI: https://doi.org/10.1038/s41746-020-00372-6