AI algorithms, in particular, require vast amounts of data to create highly accurate models. And the more high-quality data, the better. For pathologists in particular, a method called pixel-wise ...

After training on pathologists’ slide-reviewing data, the PEAN model is capable of performing a multiclassification task and imitating the pathologists’ slide-reviewing behaviors (see Panel a). The ...

The University of Nebraska–Lincoln has launched a new AI makerspace in partnership with Omaha-based Scott Data, giving ...

Government procurement contracts can be complicated, with extensive risk analysis and compliance reviews. The traditional methods of contract analytics are time-consuming and often inexact, thus ...

For pathologists in particular, a method called pixel-wise manual annotation can be used with great success to train AI models to accurately diagnose specific diseases from tissue biopsy images. This ...

anthropomorphism: When humans tend to give nonhuman objects humanlike characteristics. In AI, this can include believing a ...

AI-driven tutoring is already gaining ground through large language models such as ChatGPT, which generate quizzes, exam ...

A wave of startups are creating RL environments to help AI labs train agents. It might be Silicon Valley’s next craze in the ...

Medical image segmentation is one of the most important tasks in modern healthcare. Every pixel in a scan tells a story, whether it marks a healthy cell, a cancerous growth, or a vital organ boundary.

Imagine you are developing antibodies—drugs precisely aimed at a target, for example a viral protein or onco-marker. You test a series of antibodies and find that some work, while others do not.