Australian researchers have developed an artificial intelligence model that analyzes genetic data to identify variables associated with the risk of ischemic stroke, a step that may contribute to improving genetic risk assessment and developing more personalized prevention methods.
Euronews reported on Tuesday that researchers from the University of Technology Sydney developed the model based on "transformer" technology, which is also used in large language AI models, and were able to identify 18 genetic variables associated with ischemic stroke, the most common type of stroke.
The researchers tested the model using data from two large research cohorts comprising more than 40,000 people, and it was able to classify individuals into different categories according to their genetic risk level, while also demonstrating the ability to distinguish between levels of genetic predisposition to the disease.
The researchers explained that the model may overcome some limitations of traditional statistical methods that do not adequately capture the complex interactions between genetic variables, noting that integrating genetic information with health data and lifestyle factors may help provide a more comprehensive assessment of risk in the future.
This research falls within the efforts to deploy artificial intelligence in preventive medicine, although genetic predisposition is only one risk factor and does not mean a stroke is inevitable. Clinical application of these models requires further validation and evaluation.
Source: Syrian Arab News Agency (SANA)
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