One of the shared, fundamental goals of most chemistry researchers is the need to predict a molecule's properties, such as ...

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

Despite the AI hype, tools are proving valuable for leading-edge chip manufacturing. More aggressive feature scaling and ...

TrainCheck uses training invariants to find the root cause of hard-to-detect errors before they cause downstream problems, ...

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 ...

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 machine learning model may help predict mortality for hospitalized patients with cirrhosis at the time of admission, ...

Although they mostly go unnoticed by humans, small earthquakes occur much more frequently than large earthquakes, and knowing ...

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 ...

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

Media formulation was improved using a combination of advanced machine learning techniques, thermodynamic modeling, and ...

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