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

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

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 ...

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

While the potential benefits of AI in obesity prevention are substantial, the study devotes significant attention to ...

A new Israeli study suggests that machine-learning models may soon give growers a far more precise way to predict how much water their crops use each day, while also laying the groundwork for earlier ...

New research demonstrates that ML can also predict metre-scale laboratory earthquakes, suggesting that, when scaled, similar ...

Felimban, R. (2025) Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms.

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

Artificial intelligence is revolutionizing drug discovery and antibody engineering, accelerating the creation of new ...

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 ...

ABSTRACT: Atrial fibrillation (AF) is a leading cardiac arrhythmia associated with elevated mortality risk, particularly in low-resource settings where early risk stratification remains challenging.