The ongoing COVID-19 global pandemic is touching every facet of human lives (e.g., public health, education, economy, transportation, and the environment). This novel pan[...]

Background: Mathematical models are powerful tools to study COVID-19. However, one fundamental challenge in current modeling approaches is the lack of accurate and compre[...]

Community obesity outcomes can reflect the food environment to which the community belongs. Recent studies have suggested that the local food environment can be measured [...]

The beta-lactamase enzyme provides effective resistance to beta-lactam antibiotics due to substrate recognition controlled by point mutations. Recently, extended-spectrum[...]

Properties of spatially explicit data are often ignored or inadequately handled in machine learning for spatial domains of application. At the same time, resources that w[...]

Machine learning (ML) is being widely adopted by organizations to assist in selecting personnel, commonly by scoring narrative information or by eliminating the inefficie[...]

This paper presents a novel data-driven approach for predicting lightning-related outages that occur in power distribution systems on a daily basis. In order to develop a[...]

Aflatoxin is a carcinogenic product of mold that affects thousands of corn-producing farms in the United States every year, so being able to predict when a county will ha[...]

Background: Social media plays a critical role in health communications, especially during global health emergencies such as the current COVID-19 pandemic. However, there[...]