Predicting Preterm Birth from Cervicovaginal Metabolome of Women at High-risk: A Comparative Study Using Different Machine Learning Algorithms (2021)

First Author: David Tian

Attributed to: Application of Novel Nonlinear Data Modelling and Analysis to the Study of Cervical Impedance Spectroscopy for Preterm Birth Prediction funded by EPSRC

No abstract provided

Type: Conference/Paper/Proceeding/Abstract