Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

Kennesaw State University (KSU) is stepping into the future of workforce-ready education with the launch of a new Bachelor’s degree ...

Many small businesses use AI, but have you ever wondered how they work and where AI models get their data from?

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

According to A Survey of AI-Enabled Predictive Maintenance for Railway Infrastructure: Models, Data Sources, and Research Challenges, published in Sensors, AI-based predictive maintenance systems ...

Harshith Kumar Pedarla explores using GANs to simulate network attacks. Synthetic data augmentation improves detection scores ...

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...