Current Approaches Fall Short
There is already an ingenious array of highly effective tools, scans and procedures that can monitor the health of the heart and detect disease and damage, but technology doesn't stand still and there's always room for improvement. For example, technologies that measure the risk of death in individuals who have already suffered a heart attack are only good enough to identify a small number of resulting fatalities.
According to Zeeshan Syed, an assistant professor in the University of Michigan Department of Electrical Engineering and Computer Science and first author of a study into a computer science tool to detect heart disease, up to 70 percent of those at high risk of complications are missed. The techniques fail badly when trying to predict patients at high risk following a heart attack, therefore those that most need help go undetected.
The American Heart Association states that almost one million Americans suffer a heart attack every year, and in some age groups more than a quarter of those who survive the initial attack die of complications within a year. Typically the causes are irregular heart rhythms, which could be prevented by medications and implantable defibrillators (small battery-powered impulse generators that correct arrhythmias with a jolt of electricity).
But at the moment it is difficult to determine who's at greatest risk before it's too late. It is not an easy job. Physicians attempt to spot high risk patients with a combination of a patient's blood tests, medical history, overall health and EKG readings, but the analysis of these readings is not up to the job. All the information is actually there, it's just that only a small fraction of the data is being read. Doctors are only looking at segments that are a few seconds long.