Furqan Rustam

TL;DR: The results prove that the ES performs best among all the used models followed by LR and LASSO which performs well in forecasting the new confirmed cases, death rate as well as recovery rate, while SVM performs poorly in all the prediction scenarios given the available dataset.

TL;DR: In this paper, the authors performed Covid-19 tweets sentiment analysis using a supervised machine learning approach using a bag-of-words and the term frequency-inverse document frequency.

TL;DR: Experiments proved that the performance of machine learning classifiers is better when TF-IDF is used as the feature extraction method, and demonstrated that ensemble classifiers achieve higher accuracy than non-ensemble classifiers.

TL;DR: In this paper, an ensemble approach, called regression vector voting classifier (RVVC), was introduced to identify the toxic comments on social media platforms, which merges the logistic regression and support vector classifier under soft voting criteria.

TL;DR: A deep CNN architecture has been proposed in this paper for the diagnosis of COVID-19 based on the chest X-ray image classification, which achieved an overall accuracy as high as 99.5%.