Annotating regions of interest in medical images, a process known as segmentation, is often one of the first steps clinical ...

MIT researchers developed an interactive, AI-based system that enables users to rapidly annotate areas of interest in new biomedical imaging datasets, without training a machine-learning model in ...

Explore how machine learning is revolutionising interstitial lung disease management, enhancing early diagnosis, treatment, ...

Explore investment strategies, risks, and growth opportunities in the dynamic AI infrastructure space — plus 3 ETFs to watch.

Mînzu, V. and Arama, I. (2025) A New Method to Predict the Mechanical Behavior for a Family of Composite Materials. Journal ...

CISPA researcher Sarath Sivaprasad, together with Hui-Po Wang and Mario Fritz from CISPA and other colleagues from HIPS, has ...

AI models trained on question-answer datasets aim to lower the barrier to entry for using AI in materials science.

A research team led by the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) has built and ...

Artificial intelligence relies on machine learning algorithms trained on massive datasets to make predictions—think of how ChatGPT learned language by gorging on the internet. In biology, however, ...

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 ...