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patient clusters and digital phenotypes, leveraging machine learning approaches to identify individuals at high CV risk based on clinical and biochemical markers, immune markers, digital health data (e.g
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datasets using both traditional methods (e.g., factor analysis) as well as more modern approaches (e.g., deep learning). The goals are to develop new computational methods that allow the scientific inference
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