Technologies for Reducing Uncertainty in Estimating the Effects of Nutrition Interventions (TRUENDO) is a multi-component research project that uses different technologies to develop improved methods for estimating the effects of nutrition interventions. The project is funded by the Bill & Melinda Gates Foundation and led by the University of Washington.

The project utilizes different technologies to create improved models for projecting the outcomes of nutrition interventions. These technologies include:

-Systems modeling: This technology is used to create models that simulate the complex interactions between different factors that can affect the outcomes of nutrition interventions.

-Data mining: This technology is used to identify patterns in data that can help improve the accuracy of estimates of the effects of nutrition interventions.

-Machine learning: This technology is used to develop computer algorithms that can learn from data and improve the accuracy of estimates of the effects of nutrition interventions.

The TRUENDO project is using these technologies to develop improved methods for estimating the effects of nutrition interventions on child growth. The goal of the project is to improve the accuracy of estimates of the effectiveness of nutrition interventions, so that decision-makers can better identify which interventions are likely to be effective and invest in those interventions.