In a significant breakthrough, a team of researchers at Mount Sinai Fuster Heart Hospital has successfully developed an artificial intelligence (AI) algorithm to quickly and accurately identify patients with hypertrophic cardiomyopathy (HCM), a type of heart disease that can lead to sudden cardiac death. The algorithm, known as Viz HCM, has been approved by the Food and Drug Administration (FDA) for the detection of HCM on an electrocardiogram (ECG), and its calibration has led to a major improvement in the way this condition is diagnosed and treated.
- The Viz HCM algorithm uses advanced machine learning techniques to analyze ECG data and assign a numeric probability to the patient’s likelihood of having HCM.
- These probabilities are then used to flag high-risk patients, who require greater attention and more urgent treatment.
This innovative approach has the potential to revolutionize the way HCM is diagnosed and treated, particularly in young patients who are at a higher risk of sudden cardiac death. By providing clinicians and patients with more accurate and individualized information, the Viz HCM algorithm can help prevent complications and improve patient outcomes.
| Feature | Description |
|---|---|
| Viz HCM Algorithm | A deep-learning algorithm that analyzes ECG data and assigns a numeric probability to the patient’s likelihood of having HCM. |
| Approved by FDA | The algorithm has been approved by the Food and Drug Administration (FDA) for the detection of HCM on an electrocardiogram (ECG). |
“This is an important step forward in translating novel deep-learning algorithms into clinical practice by providing clinicians and patients with more meaningful information. Clinicians can improve their clinical workflows by ensuring the highest-risk patients are identified at the top of their clinical work list using a sorting tool,” said Joshua Lampert, Director of Machine Learning at Mount Sinai Fuster Heart Hospital.
The Viz HCM algorithm has the potential to improve patient outcomes and reduce the risk of complications associated with HCM.
The Impact of HCM
Hypertrophic cardiomyopathy (HCM) is a leading cause of heart failure and sudden cardiac death in young athletes. According to the American Heart Association, HCM affects one in 200 people worldwide. Despite its prevalence, many patients do not know they have the condition until they experience symptoms, at which point the disease may be advanced.
- HCM is a genetic disorder that affects the heart muscle, leading to abnormal heart function and potentially life-threatening complications.
- The disease may not cause symptoms until late in life, when the heart becomes severely impaired.
HCM is a significant public health concern, particularly in young athletes who are at a higher risk of sudden cardiac death. By developing an AI algorithm that can accurately identify patients with HCM, the researchers at Mount Sinai Fuster Heart Hospital hope to improve patient outcomes and reduce the risk of complications associated with this condition.
Benefits of the Viz HCM Algorithm
The Viz HCM algorithm offers several benefits, including:
- Improved accuracy: The algorithm assigns a numeric probability to the patient’s likelihood of having HCM, providing clinicians and patients with more accurate information.
- Individualized treatment: The algorithm allows for individualized treatment plans, taking into account the patient’s unique characteristics and risk factors.
- Increased efficiency: The algorithm can help clinicians prioritize high-risk patients, ensuring they receive the attention they need in a timely manner.
By providing clinicians and patients with more accurate and individualized information, the Viz HCM algorithm has the potential to revolutionize the way HCM is diagnosed and treated, particularly in young patients who are at a higher risk of sudden cardiac death.
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