Samsung’s method depends on Cadence’s Cerebrus, an AI-driven chip design automation tool that allows the designer to specify ...

The natural protein universe is vast, and yet, going beyond and designing new proteins not observed in nature can yield new ...

This study reveals how machine learning models uncover new genetic variants linked to Alzheimer’s, advancing predictive ...

Understanding and predicting complex physical systems remain significant challenges in scientific research and engineering. Machine learning models, while powerful, often fail to follow the ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

Advancements in biomedical technologies have significantly facilitated the diagnosis and monitoring of diseases. Nonetheless, traditional diagnostic ...

Researchers employed a machine learning technique known as random forest analysis and found that it significantly outperformed traditional methods in predicting which hospitalized patients with ...

A new study presents a machine learning model that accurately predicts the compressive strength of high-strength concrete, ...

Beyond machine learning, there are researchers across a wide range of fields who use link prediction and ML to conduct their research, often with profound potential impact. For example, some ...

With the new machine learning methodology, we can now extend our work to investigate how drug-carrying nanoparticles interact with blood proteins and how those interactions change the efficacy of ...