Hager Saleh

TL;DR: In this paper, an optimized Convolutional Neural Network (OPCNN-FAKE) model was proposed to detect fake news, which achieved the best performance for each dataset compared with other models.

TL;DR: In this article, a comparative study of two deep learning methods to forecast the confirmed cases and death cases of COVID-19 was performed on time series data in three countries: Egypt, Saudi Arabia, and Kuwait, from 1/5/2020 to 6/12/2020.

TL;DR: The experimental results indicate that the RF model using the unigram feature extraction method has achieved the best performance, and it is used for sentiment prediction on Twitter streaming data for coronavirus.

TL;DR: This paper compares the performance of five widely used ML algorithms, namely, the support vector machine, random forest, k-nearest neighbor, logistic regression, and decision tree to predict AD progression with a prediction horizon of 2.5 years and concludes that the random forest model achieves the most accurate performance compared to other models.

TL;DR: In this paper, a survey on the use of ML for enhancing IoT applications is presented, and an in-depth overview of the various IoT applications that can be enhanced using ML, such as smart cities, smart homes, and smart healthcare.