UC San Francisco's Center for Digital Health Innovation (CDHI), Fortanix, Intel, and Microsoft Azure have formed a collaboration to establish a confidential computing platform with privacy-preserving analytics to accelerate the development and validation of clinical algorithms.
The platform will provide a "zero-trust" environment to protect both the intellectual property of an algorithm and the privacy of health care data, while CDHI's proprietary BeeKeeperAI will provide the workflows to enable more efficient data access, transformation, and orchestration across multiple data providers.
Gaining regulatory approval for clinical artificial intelligence (AI) algorithms requires highly diverse and detailed clinical data to develop, optimize, and validate unbiased algorithm models. Algorithms that are used in the context of delivering health care must be capable of consistently performing across diverse patient populations, socioeconomic groups, geographic locations, and be equipment agnostic. Few research groups, or even large health care organizations, have access to enough high-quality data to accomplish these goals.
"While we have been very successful in creating clinical-grade AI algorithms that can safely operate at the point of care, such as immediately identifying life-threatening conditions on X-rays, the work was time consuming and expensive," said Michael Blum
