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Dietary metabolic signatures and cardiometabolic risk

Machine learning strategies were used in a study to identify individual metabolic patterns concerning diet and its long-term impact on cardiometabolic-cardiovascular disease (CM-CVD) in early adulthood. These analyses were conducted on 2,259 adults participating in the Coronary Artery Risk Development in Young Adults (CARDIA) study. The complete manuscript by Ravi V. Shah, Lyn M. Steffen, Jared…

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