Fetal Health Status Prediction During Labor and Delivery Based on Cardiotocogram Data Using Machine and Deep Learning
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-0377-1_8
Reference20 articles.
1. Petrozziello, A., Jordanov, I., Papageorghiou, A.T., Redman, C.W.G., Georgieva, A.: Deep learning for continuous electronic fetal monitoring in labor. In: 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (2018)
2. Ayres-de-Campos, D., Spong, C.Y., Chandraharan, E.: FIGO consensus guidelines on intrapartum fetal monitoring: Cardiotocography. Int. J. Gynecol. Obstet. 131, 13–24 (2015)
3. World Health Organisation Official Website, Maternal Health page https://www.who.int/health-topics/maternal-health#tab=tab_1
4. Yilmaz, E.: Fetal state assessment from cardiotocogram data using artificial neural network. J. Med. Biol. Eng. 36, 820–832 (2016)
5. Czabanski, R., Jezewski, J., Matonia, A., Jezewski, M.: Computerized analysis of fetal heart rate signals as the predictor of neonatal acidemia. Exp. Syst. Appl. 39, 11846–11860 (2012)
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