Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

Researchers used 16S rRNA sequencing and machine learning to identify gut microbiome patterns associated with insulin resistance severity in people with type 2 diabetes. XGBoost models showed that ...

The vast majority of agentic AI systems disclose nothing about what safety testing, if any, has been conducted, and many systems have no documented way to shut down a rogue bot, a study by MIT and ...

Automating knowledge production and teaching weakens the ecosystem of students and scholars that sustains universities, ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

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 ...

Ensemble integrating three architectures achieved area under the curve of 0.9208, outperforming individual models.

Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.

Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.

The Chairperson of the African Union Commission (AUC), H.E. Mahmoud Ali Youssouf, this morning conferred with the AU Deans of the Regions (Permanent Representatives of Zimbabwe, Uganda, Senegal, the ...

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 ...