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

The agency’s 31% year-over-year surge in AI use cases includes work with predictive models and surveillance technologies that sparked concern from privacy and technology safety advocates.

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 ...

In order to explore the medication rules of Shang Han Lun, this article conducted complex network analysis and cluster analysis on the 112 prescriptions in Shang Han Lun. Statistical and network ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Multi-label classification is a dynamic field within machine learning that allows a single instance to be associated with multiple labels simultaneously. Over recent years, advances in this domain ...

Phishing websites remain a persistent cybersecurity threat, exploiting users by imitating trusted online services. New ...

This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...

Cardiovascular diseases account for approximately 80% of all deaths caused by known medical conditions, making them the leading cause of mortality worldwide. The present study investigates the use of ...

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...

Real-world data typically exhibits long-tailed class distribution and contains label noise. Previous long-tail learning ...