Predicting Preterm Birth Is Not Elusive: Machine Learning Paves the Way to Individual Wellness

@inproceedings{Vovsha2014PredictingPB,
  title={Predicting Preterm Birth Is Not Elusive: Machine Learning Paves the Way to Individual Wellness},
  author={Ilia Vovsha and Ashwath Rajan and Ansaf Salleb-Aouissi and Anita Raja and Axinia Radeva and Hatim Diab and Ashish Tomar and Ronald J. Wapner},
  booktitle={AAAI Spring Symposia},
  year={2014}
}
Preterm birth is a major public health problem with profound implications on society, there would be extreme value in being able to identify women at risk of preterm birth during the course of their pregnancy. Previous research has largely focused on individual risk factors correlated with preterm birth and less on combining these factors in a way to understand the complex etiologies of preterm birth. In this paper, we use the “Preterm Prediction Study,” a clinical trial dataset collected by… CONTINUE READING

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