DataFirst and Gradient Health partner to expand access to diverse imaging data

Gradient Health and DataFirst have announced a strategic partnership designed to bridge the gap between medical data management and AI innovation.

Through this collaboration, imaging providers using DataFirst’s Silverback Workflow Engine can now seamlessly enable secure, de-identified data sharing for AI development via Gradient Health, creating new revenue opportunities while contributing to more representative and unbiased medical AI systems.

Imaging providers working with DataFirst can opt in to make their de-identified imaging data research-ready and accessible to AI developers through Gradient’s secure platform, Atlas. Participating institutions can monetise their data assets and generate recurring revenue by contributing de-identified data via the Silverback platform.

In today’s medical technology landscape, innovation depends on access to high-quality, representative data.

Without it, progress stalls, and the technologies meant to improve care risk serving only a narrow few. Gradient Health’s World Without Data initiative highlights this challenge: without participation from all types of healthcare providers, AI systems will widen health inequalities and exacerbate bias.

The partnership between Gradient Health and DataFirst helps close that gap by making participation simple, secure, and rewarding for imaging providers of every size.

“Our mission is to make medical AI both more representative and more accessible,” said Josh Miller, CEO of Gradient Health.

“Partnering with DataFirst means healthcare providers can now move from simply managing their data to actively contributing to the next generation of medical innovation while being rewarded for it.”

“Healthcare Institutions are recognising that they have currency in the digital world, and that currency is data,” said Beau Jones, CEO of DataFirst.

“Our partnership with Gradient empowers institutions with a purpose-built technology platform to access, normalise, and de-identify clinical data for research, clinical trials, and AI development.”