Microbiome-based correction for random errors in nutrient profiles derived from self-reported dietary assessments
T. Wang, Y. Fu, M. Shuai, J.-S. Zheng, L. Zhu, A. T. Chan, Q. Sun, F. B. Hu, S. T. Weiss, Y.-Y. Liu
This study introduces METRIC, a deep-learning method that uses gut microbiome data to correct random errors in self-reported dietary assessments, showing effectiveness in simulated and real-world datasets.
bioRxiv · Nov 21, 2023Microbiology