Leveraging Deep Mind’s Block Chain EMR Access Log

Machine learning (ML) offers incredible promise in the diagnosis and treatment of advanced medicine. Whether it is IBM’s Watson or Google’s DeepMind Health, it seems like many of the world’s biggest technology companies are getting involved in innovative approaches to improving patient care. One area gaining more ML healthcare interest is data privacy and security. For example, DeepMind has started to take important steps to enhance the security of clinical data by creating tamper-proof logs of access using block chains.

At Maize Analytics, we think that machine learning has a roll to play, not only to improve patient’s health, but also to improve data privacy and security. Just as ML systems can help doctors and nurses better evaluate and treat patients, Maize’s technology can empower compliance officers to better protect the privacy of patients.

Maize’s technology takes the symptoms provided by access logs – the “who,” “what,” “where,” and “when” of a record’s access – and uses novel ML techniques to determine the diagnosis of “why” the access took place. Our peer-reviewed and published work has shown that Maize can filter 95-99% of all accesses, allowing privacy officers to focus on the real threats.

We know that the work of a compliance officer can be just as stressful and high stakes as that of a doctor or nurse and that’s why we are committed to putting the same high-powered machine learning technology to work to improve outcomes.

Read more about the technology in the Compliance Today Magazine