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The authors looked at how vocabulary is impacted in Alzheimer's disease and whether it could be used a predictor of disease onset.

The authors studied the ability of deep learning models to predict droughts in the midwestern United States.

The authors looked at the correlation between C reactive protein levels and neurological deficits in patients who had suffered an ischemic stroke.

The authors looked at if there was any correlation between the phase of the moon and admissions for psychiatric concerns.

The authors assess incidence and mortality rates of two cancer types in relation to trihalomethane pollutant concentrations in drinking water.

Here the authors present an autonomous drone air filtration system that uses a novel algorithm, the gradient ascent ML particle filter (GA/MLPF), to efficiently locate and mitigate outdoor air pollution. They demonstrate that their GA/MLPF algorithm is significantly more efficient than the conventional gradient ascent algorithm, reducing both the time and number of waypoints needed to find the source of pollution.

The authors looked at different factors that influence specific gravity in beverages, including sweetener used, caffeine, carbonation, and sodium.

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.

Using machine learning to predict the risk of algae bloom

This study investigated how well food labels from 280 different brands across multiple food and drink categories in India and the US adhered to recommended nutritional labeling standards as outlined by the Codex Alimentarius.