PEDF, a pleiotropic WTC-LI biomarker: Machine learning biomarker identification and validation

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Abstract

Biomarkers predict World Trade Center-Lung Injury (WTC-LI); however, there remains unaddressed multicollinearity in our serum cytokines, chemokines, and high-throughput platform datasets used to phenotype WTC-disease. To address this concern, we used automated, machine-learning, high-dimensional data pruning, and validated identified biomarkers. The parent cohort consisted of male, never-smoking firefighters with WTC-LI (FEV1, %Pred

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Crowley, G., Kim, J., Kwon, S., Lam, R., Prezant, D. J., Liu, M., & Nolan, A. (2021). PEDF, a pleiotropic WTC-LI biomarker: Machine learning biomarker identification and validation. PLoS Computational Biology, 17(7). https://doi.org/10.1371/journal.pcbi.1009144

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