Author:
Shimoga Narayana Rao Kavitha,Asha V.
Subject
Health Informatics,Signal Processing,Biomedical Engineering
Reference42 articles.
1. MU. Khan, S. Aziz, S. Ibraheem, A. Butt, and H. Shahid, Characterization of term and preterm deliveries using electrohysterograms signatures, In: 2019 IEEE 10th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). (2019, October)0899-0905. IEEE.
2. Combination of Feature Selection and Resampling Methods to Predict Preterm Birth Based on Electrohysterographic Signals from Imbalance Data;Nieto-del-Amor;Sensors,2022
3. Granger causal analysis of electrohysterographic and tocographic recordings for classification of term vs. preterm births, Biocybernetics and Biomedical;Saleem;Engineering,2020
4. Review on EHG signal analysis and its application in preterm diagnosis;Xu;Biomed. Signal Process. Control,2022
5. R. Surendiran, R. Aarthi, M. Thangamani, S. Sugavanam, and R. Sarumathy, A Systematic Review using Machine Learning Algorithms for Predicting Preterm Birth.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献