New AI Technology Detects Hidden Heart Disorders with Basic ECG
Detecting hidden heart disorders has always been a challenge, especially for people who show no symptoms. However, a groundbreaking development in artificial intelligence (AI) has now made it possible to identify these seemingly invisible problems using basic electrocardiogram (ECG) readings.
Dr. Rohan Khera, the clinical director of the Center for Health Informatics and Analytics at the Yale School of Medicine, has successfully utilized AI to analyze ECG data and detect heart disorders that cannot be identified through conventional readings.
In an article published in the journal Circulation, Dr. Khera describes his research, which is centered in the Cardiovascular Data Science Lab. According to him, approximately one in 20 people suffer from a structural heart disorder, resulting in compromised heart function. However, they remain unaware of this condition until symptoms manifest or they require medical attention due to adverse effects.
This specific disorder, known as left ventricular systolic dysfunction, hampers the heart’s ability to pump blood effectively. It typically develops before any symptoms become evident and medical intervention becomes necessary. Dr. Khera’s study reveals that this problem can increase the risk of heart failure by more than eightfold and double the likelihood of premature death.
While there are cost-effective treatments available for this dysfunction, the challenge lies in identifying individuals who have it. Diagnosis usually requires cardiac imaging, such as an ultrasound or MRI of the heart. Unfortunately, these tests are not accessible or feasible for everyone in the community.
However, by harnessing the power of AI and deep learning in the medical field, Dr. Khera and his team have developed a groundbreaking technology that utilizes ECG data. Traditionally, ECGs measure the electrical activity in the heart and are routinely performed during physical examinations. Now, advancements have made it possible to take ECG readings using wearable devices like the Apple Watch. In fact, approximately 100 million ECGs are conducted in the United States each year.
By leveraging AI and deep learning techniques, the team has created a system that can detect hidden heart disorders by analyzing the ECG data. This groundbreaking technology presents an affordable and accessible solution for identifying individuals with left ventricular systolic dysfunction and potentially other hidden heart problems.
Dr. Khera’s research offers hope for early detection and swift intervention, which can improve outcomes and prevent complications for those at risk. Identifying individuals with hidden heart disorders before they experience symptoms or adverse effects can save lives and reduce the burden on healthcare systems.
This development in AI technology showcases the immense potential of integrating artificial intelligence into the field of healthcare. As more researchers explore the possibilities, we can expect further advancements in detecting and treating various medical conditions efficiently and effectively.
