Browse Articles

The authors looked the ability of sound sensors to predict clogged pipes when the sound intensity data is run through a machine learning algorithm.

This study explored how green spaces, climate, traffic, and air quality (GCTA) collectively influence asthma-related emergency department visits in the U.S using machine learning models and explainable AI.

Utilization of neural network to analyze Free Word Association to predict accurately age, gender, first language, and current country.

The authors looked at the presence of coliform bacteria present in ground beef after cooking it various CDC standards. They found that no coliform bacteria was present when CDC guidelines for cooking ground beef were properly followed.

The authors test different machine learning algorithms to remove background noise from audio to help people with hearing loss differentiate between important sounds and distracting noise.

The authors use pictures of candy wrappers and neural networks to improve nutritional accuracy of diet-tracking apps.

In this article the authors look at the lung microbiome in patients with cystic fibrosis to determine what the major bacterial species present are.

In this study the authors looked the trajectories of cosmic rays moving through a dipole field. They found that the trajectories of cosmic rays are determined by a particle's energy and interaction with Earth's B field.

Here, seeking to address the growing threat of multidrug-resistant bacteria (MDR). the authors used in silico virtual screening to target MDR Pseudomonas aeruginosa. They considered a key protein in its biosynthesis and virtually screened 20,000 candidates and 30 derivatives of brequinar. In the end, they identified a possible candidate with the highest degree of potential to inhibit the pathogen's lipid A synthesis.

Did the COVID-19 pandemic and travel restrictions improve air quality? The authors investigate this question in New York City using existing pollution data and forecasting trends.