Can AI Protect You From Heart Attacks?

Can AI Protect You From Heart Attacks? In recent months, there has been a significant rise in fatalities attributed to heart attacks, with a concerning trend of younger individuals succumbing to them during seemingly routine activities such as laughter, physical exercise, or recreational pursuits. These occurrences have instilled fear within communities, prompting a heightened interest in assessing cardiovascular health. Addressing these concerns, scientists have developed a novel technique utilizing Artificial Intelligence (AI) that can predict the likelihood of heart disease over the next decade. Remarkably, this predictive analysis can be performed using a single X-ray scan, offering a comprehensive assessment of an individual’s risk of experiencing a heart attack or stroke in the subsequent ten years. This breakthrough holds promise for substantially mitigating public apprehensions surrounding cardiovascular health.

Recent months have seen a notable surge in heart attack-related fatalities, with a concerning trend of even young individuals succumbing to such incidents during routine activities like laughter, exercise, or dancing. This trend has sparked widespread apprehension among the populace, prompting a keen interest in understanding heart health. In response to these concerns, scientists have developed an advanced Artificial Intelligence (AI) technique capable of predicting heart disease risk over a decade.

Remarkably, this prediction can be derived from a single X-ray scan, offering a comprehensive assessment of an individual’s likelihood of experiencing a heart attack or stroke in the coming years. This breakthrough holds promise for significantly alleviating public fears surrounding cardiovascular health.

Researchers have developed a new AI-based model that can predict irregular heartbeat, or cardiac arrhythmia, about 30 minutes before its onset. It is claimed that the model proved to be 80 percent accurate in predicting the transition from a normal cardiac rhythm to atrial fibrillation the most common type of cardiac arrhythmia in which the heart’s upper chambers (atria) beat irregularly and are out of sync with the lower ones (ventricles)

The team, including researchers at the University of Luxembourg, said that their AI model, which gives early warnings, could be easily installed in smartphones to process the data recorded on smartwatches. The warning would help the patient to take curative and protective measures to keep their cardiac rhythm stable.

It is said that WARN gave early warnings on average 30 minutes before the start of atrial fibrillation, Jorge Goncalves, from the Luxembourg Centre for Systems Biomedicine (LCSB) said “We used heart rate data to train a deep learning model that can recognize different phases — (normal) sinus rhythm, pre-atrial fibrillation, and atrial fibrillation — and calculate a ‘probability of danger’ that the patient will have an imminent episode,”

Being of low computational cost, the AI model is “ideal for integration into wearable technologies,” the researchers said, Arthur Montanari, an LCSB researcher, also said “Patients can use these devices on a daily basis, so our results open possibilities for the development of real-time monitoring and early warnings from comfortable wearable devices,”