Robert T. Chang, MD, explains how aggregated real-world data will drive practice patterns and algorithms going forward.
The final question
How does the health data get into this secure, decentralized data marketplace for AI training?
Dr. Chang explained that his efforts are focused on speed and ease of use to capture the data— for example, by taking a picture of the test result, and immediately labeling it prospectively, rather than going back to export data and label it retrospectively.
He suggested that at the point of care, when patients are receiving their result, they could immediately upload a de-identified test result to the cloud that would be available for AI training through the privacy-preserving blockchain public ledger. This would be the start of a shareable data marketplace without relying on a central owner.
“If enough people worldwide got together and started populating a database like this, it may be faster than trying to fund an international multicenter registry or get organizations to sign data sharing use agreements,” Dr. Chang concluded.
Robert T. Chang, MD
e: [email protected]
Dr. Chang has previously received AI research funding from Santen and was the recipient of a Stanford Center for Innovation in Global Health grant but has no AI financial disclosures.