Order Article Reprints

Nsugbe E, Reyes-Lagos JJ, Adams D, Samuel OW, Asogbon MG, Provost M. On the Use of Deep Learning Decompositions and Physiological Measurements for the Prediction of Preterm Pregnancies in a Cohort of Patients in Active Labor. Engineering Proceedings. 2022; 27(1):20. https://doi.org/10.3390/ecsa-9-13192

Nsugbe, Ejay, José Javier Reyes-Lagos, Dawn Adams, Oluwarotimi Williams Samuel, Mojisola Grace Asogbon, and Michael Provost. 2022. "On the Use of Deep Learning Decompositions and Physiological Measurements for the Prediction of Preterm Pregnancies in a Cohort of Patients in Active Labor" Engineering Proceedings 27, no. 1: 20. https://doi.org/10.3390/ecsa-9-13192

Nsugbe, E., Reyes-Lagos, J. J., Adams, D., Samuel, O. W., Asogbon, M. G., & Provost, M. (2022). On the Use of Deep Learning Decompositions and Physiological Measurements for the Prediction of Preterm Pregnancies in a Cohort of Patients in Active Labor. Engineering Proceedings, 27(1), 20. https://doi.org/10.3390/ecsa-9-13192