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

There is often no straightforward explanation for the various types of violence that occur around the world. In fact, even ...

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 ...

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.

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 ...

Microsoft develops a lightweight scanner that detects backdoors in open-weight LLMs using three behavioral signals, improving ...

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.

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

AI chatbots, including commercial market leaders such as ChatGPT, Google Gemini, and Claude, dispense advice that heavily ...