AliveCor and Mayo Clinic Collaborate to Identify Hidden Human Health Signals

AliveCor, the leader in FDA-cleared mobile electrocardiogram (ECG) technology for mobile devices, announced a collaboration with Mayo Clinic to utilize AliveCor’s unique measurement technology to unlock previously hidden health indicators in ECG readings. These indicators have the potential to not only improve heart health but also overall health care for a variety of conditions.
 
AliveCor provides the first consumer-ready, clinically validated and FDA-cleared ECG to give patients a more complete view of their heart health, improve proactive monitoring and create a new standard of cardiac care. By using AliveCor’s deep machine learning capabilities applied to 10 million of its user ECG recordings, Mayo Clinic and AliveCor will work together to uncover hidden physiological signals to improve heart and overall human health.
 
“Mayo Clinic has pioneered new approaches that may uncover significant measures of physiology that have been hidden in individuals’ ECGs,” said Vic Gundotra, CEO, AliveCor. “We are excited to collaborate with this team to deliver the technology behind the research that has the potential to impact the lives of millions. We look forward to transforming the way we address heart disease and bringing this technology to the market over the next year.”
 
The ECG holds a vast amount of information about a person’s overall health and applying machine learning to millions of ECG recordings is an important enhancement to the traditional ECG analysis. For example, the health indicators that are uncovered may have implications for patients who are at risk from marked changes in blood potassium levels, such as those with kidney failure. It has long been understood that dangerously abnormal potassium levels can impact the morphology of an ECG. Research by Dr. Paul Friedman, M.D. and his colleagues at the Mayo Clinic demonstrated that the ECG can be used to quantify serum potassium as a significant enhancement to traditional morphology analysis.
 
“It is exciting to see the application of machine learning algorithms in ECG and its potential to quickly detect rhythm abnormalities in patients,” said Friedman, a Mayo Clinic cardiologist who helped develop the intellectual property that went into this technology.
 
“Working with Mayo Clinic, we are hopeful that soon physicians will be turning to ECG data for the care of many types of patients, not just those with typical cardiovascular issues,” said Dr. Dave Albert, Chief Medical Officer, AliveCor.