The ECB recalibrated its economic models with AI and machine learning, forecasting 3.0% inflation and 0.8% GDP growth for ...

RNA has emerged as one of the most promising molecules in modern medicine, enabling advances from mRNA vaccines and gene ...

As artificial intelligence becomes increasingly central to modern healthcare, Nigerian statistician and AI expert Oladimeji ...

Genome-wide association studies (GWAS) have catalogued hundreds of thousands of genetic variants linked to complex human traits and diseases, with more than 625,000 variant-trait associations across ...

Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...

A representation of the cause-effect mechanism is needed to enable artificial intelligence to represent how the world works. Bayesian Networks (BNs) have proven to be an effective and versatile tool ...

A year ago today, a violent storm struck the coast of the sleepy Sicilian fishing village of Porticello. High winds and dramatic thunder and lightning are not unheard of around this time of year in ...

Accurate disaster prediction combined with reliable uncertainty quantification is crucial for timely and effective decision-making in emergency management. However, traditional deep learning methods ...

Researchers at The University of Texas at Arlington have developed a new computational tool that helps scientists pinpoint proteins known as transcriptional regulators that control how genes turn on ...

Abstract: Identifying handwritten words poses a complicated problem owing to the variances in handwriting styles and the possible noise and distortions present in the data. The performance of used ...

Predicting the adhesive force between steel reinforcement and concrete is crucial as it influences stress distribution and the overall mechanical behavior of reinforced concrete. This study proposes a ...