Artificial intelligence is already helping clinicians spot patterns in diagnostic images and detect signs of disease. But many of today’s pathology AI systems are built for a single task and must be rebuilt for each new application.
A study recently published in Nature Medicine describes a different approach aimed at advancing research in this field. Researchers from Microsoft Research and Paige, now part of Tempus, developed PRISM2, a pathology foundation model trained on both tissue images and language based on real pathology reports. The goal was to help AI learn from the large amount of available text data and create a system that could support future pathology research and development.