Combine AI With ECG For Early Detection Of Heart Conditions
Chander Sinha - Jan 11, 2019
Researchers are looking for a new way to detect heart conditions and they are feeling very positive with AI in combination with the Electrocardiogram.
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A new study shows that detecting a heart condition is possible through applying AI (Artificial Intelligence) to an inexpensive and widely available test.
According to the researchers from the Mayo Clinic of Minnesota, using Artificial Intelligence alongside the ECG (Electrocardiogram) leads to not only an affordable but also an early and simple indicator of asymptomatic left ventricular dysfunction that is prone to be diagnosed with less accessible as well as costly imaging tests, like CT, MRI or echocardiograms scans.

This kind of dysfunction can be detected by the existence of a somewhat weak heart pump carrying quite a high risk of causing heart failure that is related to the reduction in longevity as well as living quality.
The study has shown that asymptomatic left ventricular dysfunction can be reliably detected when we apply Artificial Intelligence to a standard Electrocardiogram.
Paul Friedman from the Mayo Clinic expressed:

Digital data collected from 625,326 persons is used for the study where the team paired electrocardiogram with transthoracic echocardiograms.

Research that has been published in Nature Medicine shows that the AI/ECG test has a favorable accuracy compared with some other screening tests that most of us have heard of like cervical cytology (cervical cancer), mammography (breast cancer) as well as prostate-specific antigen (prostate cancer).
Additionally, the result showed that patients who did not have ventricular dysfunction but still got positive in Artificial Intelligence screen we had the risk of having ventricular dysfunction in the future four times higher than those who got the negative screen.
Friedman said:

Noted that according to the study that once it is identified, the asymptomatic left ventricular dysfunction will very likely be treatable.
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