June 22, 2022 — Gradient Health, a medical technology company based in North Carolina, announced a new initiative which will give academic researchers open access to their vast and diverse medical imaging datasets, accelerating high quality research into AI for healthcare.
Medical researchers are often held back by a lack of easy access to large, unbiased datasets. Gradient Health’s platform provides instant access to a vast database of ethically sourced anonymized medical imagery. This enables researchers to quickly search for the data they need, access pre-labeled images, and develop AI algorithms that are based on truly representative data.
Early adopters of the technology as part of this initiative include world leading research institutions such as Stanford University and Duke University.
Kevin Wu and Eric Wu from Stanford University are investigating bias within radiology AI. So far Gradient have delivered over 10,000 images of chest x-rays for them to study. They have particularly chosen to work with Gradient due to the speed they are able to deliver large datasets and the diversity of the data.
“AI algorithms are increasingly used in clinical care — however, an often under looked question is whether these models perform well on patients from underrepresented populations.” Comments Eric Wu, “We’re excited to be working with the Gradient Health team and their diverse datasets toward making medical AI more fair and equitable.”
Josh Helmkamp, MD, at Duke University is partnering with Gradient Health to further research into orthopedics.
Josh Miller, CEO, Gradient Health comments “Research that aims to save lives shouldn’t benefit select groups- and to make sure that doesn’t happen, we need to make sure researchers have diverse and readily available data. That’s the only way we can improve quality and bring down the cost of care – for everyone.”