Robert T. Chang, MD, explains how aggregated real-world data will drive practice patterns and algorithms going forward.
Blockchain technology involves decentralized sharing of information without a centralized owner, such as a Google or Facebook. The first mainstream association of the term “blockchain” was with bitcoin.
However, blockchain is really a platform technology, Dr. Chang explained.
“Basically, it is a type of shared public database across many computers, with no single owner, that records a series of time-sequenced, permanent transactions, which people can trust to be secure,” he said.
What makes the blockchain technology special is that it is updated in real time across many computer nodes, with a competitive, mathematically based validation system to verify the transactions “AKA blocks.”
The trust comes from the fact that it is too expensive for the shared database ledger to be manipulated, and thus the first use case was a decentralized digital currency record-keeping system.
In the healthcare realm, using blockchain platform technology combined with encryption, users can submit private image data, for example, which can be shared without actually becoming public domain.
Then, through secure computation, the image data can be used to train or validate AI algorithms without letting any user actually download the original data. This is the concept of the privacy-preserving blockchain as a platform for training and testing AI algorithms. Then a validation set can truly stay private.
“The key factor that attracts people to blockchain technology is that there is no centralized owner, and, thus, information stored on it cannot be manipulated by anyone without taking down the entire system,” Dr. Chang said.
Robert T. Chang, MD
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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.