Scientists who use imaging to understand the brain's complexity often focus on the strongest signals and ignore the rest. But this strategy, researchers warn, may reveal only the tip of the iceberg. A ...

Innovative machine learning models using routine clinical data offer superior stroke risk prediction in atrial fibrillation, ...

Researchers have developed a feature selection-based solar irradiance forecasting method to improve the operation of ...

Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...

This gorgeous brick structure looks like it was built by people who actually cared about architecture, back when buildings ...

A new study published in Genome Research presents an interpretable artificial intelligence framework that improves both the accuracy and transparency of genomic prediction, a key challenge in fields ...

Cardiovascular disease (CVD) remains the foremost contributor to global illness and death, underscoring the critical need for effective tools that can predict risk at early stages to support ...

Factoring out nucleotide-level mutation biases from antibody language models dramatically improves prediction of functional mutation effects while reducing computational cost by orders of magnitude.

Abstract: Birth weight is a vital indicator of pregnancy progress and infant development. Accurate pre-delivery estimation is crucial, influencing both short- and long-term health outcomes. This study ...

Bacteriocins offer a promising solution to antibiotic resistance, possessing the ability to target a wide range of bacteria with precision. Thus, there is an urgent need for a computational model to ...