Researchers at Microsoft, Providence Health System and the University of Washington say they’ve developed a new artificial intelligence model for diagnosing cancer, based on an analysis of more than a billion images of tissue samples from more than 30,000 patients.
The open-access model, known as Prov-GigaPath, is described in research published today by the journal Nature and is already being used in clinical applications.
“The rich data in pathology slides can, through AI tools like Prov-GigaPath, uncover novel relationships and insights that go beyond what the human eye can discern,” study co-author Carlo Bifulco, chief medical officer of Providence Genomics, said in a news release. “Recognizing the potential of this model to significantly advance cancer research and diagnostics, we felt strongly about making it widely available to benefit patients globally. It’s an honor to be part of this groundbreaking work.”
The effort to develop Prov-GigaPath used AI tools to identify patterns in 1.3 billion pathology image tiles obtained from 171,189 digital whole-slides provided by Providence. The researchers say this was the largest pre-training effort to date with whole-slide modeling — drawing upon a database five to 10 times larger than datasets such as the The Cancer Genome Atlas.
