Driven by a plethora of benefits, data sharing is gradually becoming a “must have” for advanced device nodes and multi-die ...

To create their contactless approach, the researchers created a machine learning algorithm capable of analyzing aspects of ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to ...

The problem comes down to how these tools learn. New study reveals unexpected results after using AI tools to predict extreme ...

In the past decade, cloud-scale analytics tools have transformed the digital fight against deforestation. Instead of manual ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Buildings produce a large share of New York's greenhouse gas emissions, but predicting future energy demand—essential for ...

The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...

When pitching the use of a model, data scientists rarely report on its potential value. They then experience an unnerving ...