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for predicting CACS with only laboratory data in healthy participants. Xgboost ML algorithm was found to be a more reliable predictor of CACS in healthy participants compared to the BLR algorithm. ML algorithms may be useful for predicting CACS with only laboratory data in healthy participants.The aim of this paper is to understand public preferences for several future scenarios of achieving a healthier, more equitable and sustainable Europe, which differ in the way the society is organized (individualistically vs. collectively) and in