Nieto-del-Amor, F.; Prats-Boluda, G.; Martinez-De-Juan, J.L.; Diaz-Martinez, A.; Monfort-Ortiz, R.; Diago-Almela, V.J.; Ye-Lin, Y.
Optimized Feature Subset Selection Using Genetic Algorithm for Preterm Labor Prediction Based on Electrohysterography. Sensors 2021, 21, 3350.
https://doi.org/10.3390/s21103350
AMA Style
Nieto-del-Amor F, Prats-Boluda G, Martinez-De-Juan JL, Diaz-Martinez A, Monfort-Ortiz R, Diago-Almela VJ, Ye-Lin Y.
Optimized Feature Subset Selection Using Genetic Algorithm for Preterm Labor Prediction Based on Electrohysterography. Sensors. 2021; 21(10):3350.
https://doi.org/10.3390/s21103350
Chicago/Turabian Style
Nieto-del-Amor, Félix, Gema Prats-Boluda, Jose Luis Martinez-De-Juan, Alba Diaz-Martinez, Rogelio Monfort-Ortiz, Vicente Jose Diago-Almela, and Yiyao Ye-Lin.
2021. "Optimized Feature Subset Selection Using Genetic Algorithm for Preterm Labor Prediction Based on Electrohysterography" Sensors 21, no. 10: 3350.
https://doi.org/10.3390/s21103350
APA Style
Nieto-del-Amor, F., Prats-Boluda, G., Martinez-De-Juan, J. L., Diaz-Martinez, A., Monfort-Ortiz, R., Diago-Almela, V. J., & Ye-Lin, Y.
(2021). Optimized Feature Subset Selection Using Genetic Algorithm for Preterm Labor Prediction Based on Electrohysterography. Sensors, 21(10), 3350.
https://doi.org/10.3390/s21103350
