Analysis on novel coronavirus (COVID-19) using machine learning methods

Spatio-temporal estimation of the daily cases of COVID-19 in worldwide using random forest machine learning algorithm

“…Epidemiological, statistical and mathematical models have also been introduced to predict the distribution, to observe the changes depending on meteorological conditions, and to examine the structure of this epidemic which affects all countries globally [14] , [15] , [16] , [17] , [18] , [19] , [20] , [21] . Besides, the performance of machine learning approaches for the diagnosis and treatment of the disease was also studied [22] , [23] , [24] , [25] , [26] , [27] , [28] . All these studies reveal the general structure of such an epidemic and disease that humanity has not encountered before and its effects on society.…”

A novel adaptive deep learning model of Covid-19 with focus on mortality reduction strategies

“…The novelty of this paper lies in the use of real-time online incremental learning technique in epidemic disease modeling. Many machine learning techniques have been used in epidemic disease modeling [36] , however, this paper is the first instance of development of an incremental learning algorithm as a real-time adaptive deep learning technique for parameter estimation of an epidemiological model thus providing the model with the capability to work online i.e, unlike typical machine learning techniques, it doesn’t require to rebuild or retrain the model from scratch every time a new data set is received but intelligently adapts the model to ever-changing infection dynamics. Since the model is non-intrusive, adaptive, intelligent, real-time and online in nature, therefore it can be employed to monitor, forecast and simulate the growth of any infectious disease over a large-sized population without losing accuracy, fidelity or computational performance due to limitations like run-time duration, size of training data, computational complexity, change in transmission dynamics due to mutations in virus or bacteria, change in prevention mechanisms or government policies.…”

Forecasting COVID-19 cases in Algeria using logistic growth and polynomial regression models

“…Usually polynomial regression is used for the short term prediction. This type of model was widely used in the case of COVID-19 [20,21,22,23,24] and has shown an excellent accuracy in certain cases [25].…”