Scikit-learn, PyTorch, and TensorFlow remain core tools for structured data and deep learning tasks.New libraries like JAX, Polars, and LangChain ...

Explore how AI predictive analytics reshapes industries by providing insights, forecasting trends, and enhancing ...

Machine learning interview questions now focus on both theory and real-world applications.Understanding basics like overfitting, bias, and regres ...

According to the Virginia Department of Health (VDH), drug overdose deaths among Virginia residents decreased by 43% in 2024.

FinRegLab today released new empirical research demonstrating that adopting machine learning techniques and incorporating ...

Previous methods struggle to incorporate real-time data or account for nonlinear interactions among macroeconomic variables. This leaves a critical gap in anticipating fiscal stress events. Machine ...

AI-based analytics form the most impactful pillar in the model, enabling digital twins to conduct pattern recognition, demand ...

Community health nurses can enhance the elderly's quality of life (QoL) through personalized care, lifestyle counselling, and preventive measures. The primary objective of this study was to develop ...

Machine learning models show promise in predicting colorectal cancer and advanced polyps, but validation gaps remain.

Artificial intelligence models used to detect depression on social media are often biased and methodologically flawed, ...

Objective Long-term azithromycin treatment effectively prevents acute exacerbations of chronic obstructive pulmonary disease ...

Objectives The association between smoking and patients with schizophrenia has been established through epidemiological ...