Comparison of the csEN algorithm to existing predictive methods and model reduction. Comparison of the csEN algorithm to existing predictive methods and.

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Presentation transcript:

Comparison of the csEN algorithm to existing predictive methods and model reduction. Comparison of the csEN algorithm to existing predictive methods and model reduction. (A and B) Comparison of the predictive power of existing algorithms for the estimation of gestational age at time of sampling in the training cohort (A) (n = 18) and the validation cohort (B) (n = 10). Algorithms included Support Vector Machine (SVM), EN, LASSO, randomForest, and k-nearest neighbors (KNN). (C) The dot plot depicts the number of csEN model components versus the P value of the csEN model for predicting gestational age. Red lines indicate the piece-wise regression fit for identification of a breakpoint indicating that 25 features are required for highest statistical stringency. (D) Location of the 25 features in the correlation network. Nima Aghaeepour et al. Sci. Immunol. 2017;2:eaan2946 Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).