Academic institutions operate in an extremely demanding and competitive environment. Some difficulties confronting most schools are delivering high-quality education to the students, developing systems for evaluating student performance, analyzing performance, and recognizing the future demands...

Artificial neural networks (ANNs) are commonly used to solve nonlinear problems. ANNs are composed of parallel interconnected layers that include processing elements called neurons. These neurons use mathematical functions to process the data, mimicking the human brain. In this study, we use...

The study's objective is to check whether the predictive power of Machine Learning Techniques is better than Logistic Regression in predicting the bankruptcy of firms and that the same predictive power of ascertaining bankruptcy improves when a proxy for uncertainty is added to the model as a...

The valuation of house prices is drawing noteworthy attention due to worldwide financial and real estate crises in the last decade. Therefore, there is an immediate need to design more effective predictive systems of house prices. Indeed, investors, creditors, and governments are all interested...

Social media data are increasingly being studied for their potential use in addressing and mitigating public health issues. Data from text and image-based social media have been used for observational and intervention studies, and have been collected from a variety of social media platforms....

Technology application in healthcare is a recent field devoted to sustainability in the healthcare industry. However, research in this sector has grown at a rapid pace. While this expansion has been advantageous for the discipline, it has also made it more difficult to grasp its extent. As a...