Machine Learning Approach for Pre-Eclampsia Risk Factors Association
Machine Learning Approach for Pre-Eclampsia Risk Factors Association
Antonieta Martínez-Velasco,María de Lourdes Martínez-Villaseñor,Luis Miralles-Pechuán
2018 · DOI: 10.1145/3284869.3284912
International Conference on Smart Objects and Technologies for Social Good · 11 Citations
TLDR
This work has created a supervised model to predict if a patient suffers preeclampsia, which has been optimized by selecting the best features and by optimizing the threshold when predicting a class.