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| 67 | <h2>Conflicts of Interest</h2> |
67 | <h2>Conflicts of Interest</h2> |
| 68 | <p>No conflict of interest was declared. The funder had no role in study design, data collection, analysis, or publication.</p> |
68 | <p>No conflict of interest was declared. The funder had no role in study design, data collection, analysis, or publication.</p> |
| 69 | 69 | ||
| 70 | <h2>References</h2> |
70 | <h2>References</h2> |
| 71 | <p>[References 1-11 available in original documentation.]</p> |
71 | Antoine, C. & Young, B. K. (2020). Cesarean section one hundred years 1920–2020: The good, the bad and the ugly. Journal of Perinatal Medicine, 49(1), 5–16, https://doi.org/10.1515/jpm-2020-0305 |
| 72 | 72 | Dahlen, H. G., Thornton, C., Downe, S., de Jonge, A., Seijmonsbergen-Schermers, A., Tracy, S., Tracy, M., Bisits, A. & Peters, L. (2021). Intrapartum interventions and outcomes for women and children following induction of labour at term in uncomplicated pregnancies: A 16-year population-based Linked Data Study. BMJ Open 11, e047040, https://doi.org/10.1136/bmjopen-2020-047040 |
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| 73 | Mas-Cabo, J., Ye-Lin, Y., Garcia-Casado, J., Díaz-Martinez, A., Perales-Marin, A., Monfort-Ortiz, R., Roca-Prats, A., López-Corral, A. & Prats-Boluda, G. (2020). Robust Characterization of the Uterine Myoelectrical Activity in Different Obstetric Scenarios. Entropy 22, 743, https://doi.org/10.3390/e22070743 |
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| 74 | Alberola-Rubio, J., Garcia-Casado, J., Prats-Boluda, G., Ye-Lin, Y., Desantes, D., Valero, J. & Perales, A. (2017). Prediction of labor onset type: Spontaneous vs induced; role of electrohysterography? Computer Methods and Programs in Biomedicine 144, 127–133, https://dx.doi.org/10.1016/j.cmpb.2017.03.018 |
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| 75 | Benalcazar-Parra, C., Ye-Lin, Y., Garcia-Casado, J., Monfort-Ortiz, R., Alberola-Rubio, J., Perales, A. & Prats-Boluda, G. (2019). Prediction of labor induction success from the uterine electrohysterogram. Journal of Sensors 2019, ID 6916251, https://doi.org/10.1155/2019/6916251 |
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| 76 | Fergus, P., Selvaraj, M. & Chalmers, C. (2018). Machine learning ensemble modelling to classify caesarean section and vaginal delivery types using Cardiotocography traces. Computers in Biology and Medicine 93, 7–16, https://doi.org/10.1016/j.compbiomed.2017.12.002 |
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| 77 | Jager, F. (2023). An open dataset with electrohysterogram records of pregnancies ending in induced and cesarean section delivery. Scientific Data. 10, Article number: 669, https://doi.org/10.1038/s41597-023-02581-6 |
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| 78 | Fele-Žorž, G., Kavšek, G., Novak-Antolič, Ž. & Jager, F. (2008). A comparison of various linear and non-linear signal processing techniques to separate uterine EMG records of term and pre-term delivery groups. Med Biol Eng Comput, 46, 911–922, https://physionet.org/content/tpehgdb/1.0.1/tpehgdb.pdf |
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| 79 | Jager, F., Libenšek S. & Geršak, K (2018). Characterization and automatic classification of preterm and term uterine records. PLoS ONE 13(8):e0202125. https://doi.org/10.1371/journal.pone.0202125 |
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| 80 | Pirnar, Ž., Jager, F. & Geršak, K. (2022). Characterization and separation of preterm and term spontaneous, induced, and cesarean EHG records. Computers in Biology and Medicine, 151, 106238. https://doi.org/10.1016/j.compbiomed.2022.106238 |
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| 81 | "Slovenian Research Agency (ARRS)" https://www.arrs.gov.si/ [Accessed 08/26/2023] |