Humans are good at deciphering complex images, compared to computers. Until recently, internet users often needed to verify that they were human by completing a CAPTCHA security check. A familiar variety asked the user to check all the boxes that contain a car, or a street sign.
If we asked random people off the street to look at pathology slides and “quick, check all the boxes that contain tumor cells,” what would happen? The accuracy, compared to a trained pathologist, wouldn’t be very good.
This challenge of expertise – crowdsourcing and pathology are not immediately compatible – is what Lee Cooper and colleagues sought to overcome in a recent paper published in Bioinformatics. So they put together something they called “structured crowdsourcing.”
“We are interested in describing how the immune system behaves in breast cancers, and so we built an artificial intelligence system to look at pathology slides and identify the tissue components,” Cooper says.
Dr. Cooper is a faculty member in the CB program.
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