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From : http://www.csail.mit.edu/node/1623

Researchers from MIT CSAIL, the University of Michigan, Brigham and Women’s Hospital in Boston and Harvard Medical School have developed a new tool that can more accurately determine risk of death in patients who have suffered a heart attack. Results of the study could prove life saving for the millions of Americans who suffer heart attacks every year.

The new technique involves searching for subtle indicators of risk hidden in a patient’s electrocardiogram (EKG or ECG) history. The electrocardiogram measures and displays the electrical activity of the heart. Current techniques for determining risk of death in patients who have suffered a heart attack tend to only identify a small portion of resulting fatalities.

Zeeshan Syed, Assistant Professor of Computer Science and Engineering, was recently awarded an National Science Foundation CAREER grant for his research project, "Computationally Generated Biomarkers." The CAREER grant is one of NSF's most prestigious awards, conferred for "the early career-development activities of those teacher-scholars who most effectively integrate research and education within the context of the mission of their organization."

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Instrumenting patients with small, wearable sensors will enable physicians to continuously monitor patients outside the hospital. These devices can be used for real-time classification of the data they collect. For practical purposes, such devices must be comfortable and thus be powered by small batteries. Since classification algorithms often perform energy-intensive signal analysis, power management techniques are needed to achieve reasonable battery lifetimes.

The human body and the systems that maintain it are, at their most basic, bundles of crackling electricity. Impulses, currents and waves can be found in every part of our world, and they offer much in the way of information if they can be properly read and interpreted. At the abstract level, Professor John Guttag and his research team are engaged in applied signal processing. But the marriage they have made between computer systems and medical research is vigorous and thriving. While it has already spawned impressive accomplishments, the most exciting opportunities to positively impact the practice of medicine lie in the team’s future.

A new approach to analyzing electrocardiograms--a ubiquitous test of the heart's electrical function--could predict who is most likely to die after a heart attack. Researchers at MIT found that measuring how much the shape of the electrical waveform varies from beat to beat identifies high-risk patients better than existing risk factors. If the findings hold up in further clinical trials, the technology could be used to figure out which heart attack patients need the most aggressive treatment.