The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Mount Sinai researchers showed that deep learning applied to standard ECGs accurately detected chronic obstructive pulmonary ...

DiaCardia, a novel artificial intelligence model that can accurately identify individuals with prediabetes using either ...

Mount Sinai analysis looks at the effectiveness of electrocardiograms analyzed via deep learning as a tool for early COPD detection ...

An analysis by The Marshall Project provides a window into what causes thousands of people to die in prisons and jails every ...

As drones survey forests, robots navigate warehouses and sensors monitor city streets, more of the world's decision-making is ...

By adopting a Data-First approach, you can build connected intelligence while providing AI analysis to automate ...

Dr Michele Orini shares how machine learning can help identify critical VT ablation targets for a safer, data-driven ...

The orbitofrontal cortex (OFC) is critical to identifying task structure and to generalizing appropriately across task states with similar underlying or hidden causes. This capability is at the heart ...

A generative AI system can now analyze blood cells with greater accuracy and confidence than human experts, detecting subtle signs of diseases like leukemia. It not only spots rare abnormalities but ...

Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality globally. Effective management hinges on early diagnosis, which is often impeded by non-specific symptoms and ...