Machine-learning models identify relationships in a data set (called the training data set) and use this training to perform operations on data that the model has not encountered before. This could ...

DeNovix discusses how customer demand inspired the development of specialized CellDrop applications for hepatocytes and ...

An AI system that can predict what a patient's knee X-ray will look like a year in the future could transform how millions of ...

The integration of AI and IoT has transformed farming into a dynamic data ecosystem, where predictive insights replace ...

As artificial intelligence (AI) use continues to grow in nearly every industry, it is important to establish guardrails to ...

The study departs from conventional mean-based economic forecasting by focusing on quantile prediction, a technique that ...

The field of computational materials science has been profoundly transformed by integrating deep learning and other machine learning methodologies. These sophisticated data-driven approaches have ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, ...

This predictive model built on readily acquired clinical data provides encouraging results for the detection of residual disease. External validation and prospective studies implementing the model in ...

We retrospectively identified 111 lesions, divided into training and test sets (n = 78 v 33) with equal class distribution. 3D Slicer was used to segment lesions with a short axis of >10 mm from the ...