Researchers at Karolinska Institutet, Uppsala University, and several European universities have found that artificial intelligence (AI) could play a role in identifying the risk of cardiovascular disease, specifically atherosclerosis.
The study, published in Cardiovascular Research, could pave the way for more accurate diagnostics and early interventions.
Atherosclerosis, a buildup of fats, cholesterol, and other substances in the arteries, often leads to heart attacks or strokes.
Being a silent killer, atherosclerosis is a common cause of cardiovascular diseases, and its early identification can significantly contribute to preventing serious health consequences.
How AI Can Help
The research team used clinical and molecular data together with ultrasound measurements of the carotid artery from participants in a large European study.
Using an unsupervised method of machine learning, they integrated all the data to define four endotypes to identify individuals with low, medium, or high risk of heart attack and stroke.
The AI-generated endotypes were tested to predict the risk of developing atherosclerosis in the carotid artery.
The results have been validated in a Swedish cardiovascular study, showing that the AI model can predict atherosclerosis risk to a certain extent.
The team now plans to investigate the genes and mechanisms behind the different endotypes of atherosclerosis and related heart and brain diseases.
They also aim to explore how the study’s findings can be utilized to predict the development of atherosclerosis in other vascular areas.
According to Bruna Gigante, the senior lecturer at Karolinska Institutet, these findings could lead to precision medicine in preventing cardiovascular diseases related to atherosclerosis.
The ability to predict atherosclerosis risk at an individual level could provide an opportunity to intervene before the disease develops, potentially saving numerous lives.
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The study was published in Cardiovascular Research.
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