This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within ...

An analysis spanning fifty years reveals that the cost of gasoline is one of the strongest predictors of presidential approval ratings, acting in an uneven pattern where initial price spikes cause the ...

Long-term lithium therapy remains the most effective maintenance treatment for bipolar disorder, yet it poses a significant risk of progressive renal impairment in a subset of patients. Early ...

Machine learning algorithms help computers analyse large datasets and make accurate predictions automatically.Classic models like regression, dec ...

Balancing nitrogen use is critical for maximizing crop yield while minimizing environmental and economic costs. A new approach integrates drone-based multispectral imaging with machine learning to ...

A new study explores how artificial intelligence models can support clinical decision-making for sepsis management. Their research, titled “Responsible AI for Sepsis Prediction: Bridging the Gap ...

Abstract: In this paper, we evaluate the effectiveness of the Random Forest algorithm in detecting intrusions within IoT environments through features selection analysis. We utilize the Network ...

Abstract: In this work, the Random Forest and SARIMA methods were used, both optimized through genetic algorithms, with the purpose of forecasting wind speed and, consequently, energy production. The ...

The use of machine learning (ML) and artificial intelligence (AI) in power converters represents the latest development in ...

Machine learning algorithms may accurately predict inborn errors of immunity (IEI) in children with persistently low serum IgE.

Researchers report that the integration of machine learning and Internet of Things (IoT) technologies is enabling a new generation of intelligent industrial environments capable of real-time ...