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. 2022 Aug 23;10:893059. doi: 10.3389/fped.2022.893059

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Copyright © 2022 Casaburi, Wei, Kazi, Liu, Wang, Tao, Lin, Dunn, Henrick, Frese and Sylvester.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Machine learning revealed NEC microbiome signatures by post-menstrual age. (A) Pathway level data was stratified by species, oversampled to balance NEC classes, sub-setted by PMA, and trained on different model algorithms to explore model performance. Models sub-setted to include only samples from subjects with a PMA ≥29 weeks performed moderately better with respect to specificity and sensitivity than their counterparts. (B) Principal coordinate analysis (PCoA) of all samples based on weighted UniFrac distance and colored by Necrotizing Enterocolitis (NEC) or preterm infants without NEC (Preterm).