Adaptive testing in integrated circuits (ICs) has emerged as an innovative strategy to optimise and streamline the evaluation of increasingly complex semiconductor devices. By incorporating machine ...

Researchers claim model can cut years from testing cycles Scientists have developed a machine learning method that could dramatically slash the cost and energy required to develop new lithium-ion ...

Development and Validation of an Ipsilateral Breast Tumor Recurrence Risk Estimation Tool Incorporating Real-World Data and Evidence From Meta-Analyses: A Retrospective Multicenter Cohort Study Data ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...

Machine learning models are usually complimented for their intelligence. However, their success mostly hinges on one fundamental aspect: data labeling for machine learning. A model has to get familiar ...

Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and microfluidics to nanomaterial testing, thanks to their compact size and ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 possible variants-more combinations than atoms in the observable universe.

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

The researchers suggest that this improvement in diagnostic performance for OFC biomarker discovery can be used to develop a diagnostic alternative for food allergy that is scalable and more efficient ...