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

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 ...

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 ...

Learn how Microsoft research uncovers backdoor risks in language models and introduces a practical scanner to detect ...

A new proposal suggests using existing semantic HTML to mark sections of a page that are AI generated for EU regulatory ...

Traditional processes used to discover new materials are complex, time-consuming, and costly, often requiring years of ...

A novel multi-task XGBoost model shows robust overall performance in predicting antimicrobial resistance in common gram-negative pathogens.

Apple researchers figured out a way to speed up AI speech generation from text without sacrificing audio quality or breaking intelligibility.

Although large language models (LLMs) have the potential to transform biomedical research, their ability to reason accurately across complex, data-rich domains remains unproven. To address this ...