New Model Accurately Estimates Energy Intake from Dietary Surveys
A team of international researchers, led by Prof. John Speakman, has developed a novel predictive model to screen misreporting in dietary surveys. This innovative approach combines classical statistics and machine learning to estimate energy expenditure, providing a more objective method for assessing the validity of food intake records. Currently, nutritional epidemiology relies on self-reported data … Read more