"Range anxiety" remains one of the major issues of electric vehicles (EVs). Most of the existing range prediction technologies rely on simulated conditions or limited datasets, making it difficult to ...

Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...

A new study published in the International Journal of General Medicine showed that physicians may reliably estimate the ...

According to a new study, machine learning can reliably identify patients at high risk of early dysphagia following acute ...

Artificial intelligence has become both the weapon and the shield in today’s cyber battlefield. From self-learning malware to adaptive firewalls, AI is reshaping the balance of power between attackers ...

Researchers identified distinct demographic, clinical, and serologic predictors of incident LVSD and cardiac recovery among patients with SSc.

Accurate classification of wetland vegetation is essential for biodiversity conservation and carbon cycle monitoring. This study developed an adaptive ...

The review reports that blockchain-enhanced federated learning systems typically achieve slightly lower raw accuracy than ...

A new statistical analysis of Nigeria’s 2023 elections says Labour Party (LP) strongholds recorded the highest concentration of irregularities in the polls.

Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.

Economic variables also play a central role. Rising GDP per capita increases healthcare utilization rates as households are ...

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.