Cardiovascular disease, including conditions like atherosclerosis, remains a leading cause of death globally.
Researchers at Karolinska Institutet, in collaboration with other universities, have explored the potential of artificial intelligence (AI) in identifying individual risks of atherosclerosis—a key contributor to heart attacks and strokes.
This groundbreaking study, published in Cardiovascular Research, offers a glimpse into how AI may enhance diagnostic accuracy and contribute to preventive healthcare.
Understanding Atherosclerosis: Atherosclerosis is a prevalent condition characterized by the accumulation of fats, cholesterol, and other substances on artery walls.
Over time, this plaque buildup can narrow arteries, impeding blood flow and leading to acute events like heart attacks and strokes.
Precision Medicine for Prevention: The study conducted at Karolinska Institutet sought to leverage AI to assess an individual’s risk of developing atherosclerosis.
The ultimate goal is to intervene and prevent cardiovascular diseases before they manifest clinically.
The Research Method: Researchers collected clinical and molecular data and performed ultrasound measurements of the carotid artery in participants from a large European study.
An unsupervised machine learning approach integrated this diverse dataset to identify distinct risk groups, or “endotypes,” based on the individual’s risk of heart attack and stroke.
Three Risk Groups: The AI-driven analysis categorized individuals into three risk groups: low, medium, and high risk of atherosclerosis. These endotypes were validated using standard epidemiological and statistical methods in a Swedish cardiovascular study.
Promising Results: The study demonstrated that AI-generated endotypes could predict the risk of developing atherosclerosis in the carotid artery to some extent.
This suggests the potential of AI to enhance risk assessment and facilitate early interventions for individuals at higher risk of cardiovascular disease.
Future Directions: The research team plans to delve deeper into the genetic and mechanistic aspects of different atherosclerosis endotypes and their associations with heart and brain-related diseases.
Additionally, they aim to explore how these findings can be applied to predict atherosclerosis development in other vascular areas.
Conclusion: Artificial intelligence has emerged as a valuable tool in identifying the risk of cardiovascular disease, specifically atherosclerosis.
By categorizing individuals into distinct risk groups, AI-driven precision medicine approaches hold the promise of early intervention and more effective prevention strategies.
Further research into the genetic and mechanistic underpinnings of atherosclerosis endotypes may lead to more targeted and personalized healthcare in the fight against cardiovascular disease.
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The research findings can be found in Cardiovascular Research.
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