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For: Sarkar P, Lobmaier S, Fabre B, González D, Mueller A, Frasch MG, Antonelli MC, Etemad A. Detection of maternal and fetal stress from the electrocardiogram with self-supervised representation learning. Sci Rep 2021;11:24146. [PMID: 34921162 DOI: 10.1038/s41598-021-03376-8] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 6.0] [Reference Citation Analysis]
Number Citing Articles
1 Wakefield C, Yao L, Self S, Frasch MG. Wearable technology for health monitoring during pregnancy: an observational cross-sectional survey study. Arch Gynecol Obstet 2022. [PMID: 35831759 DOI: 10.1007/s00404-022-06705-y] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
2 Siew HSH, Alshebly YS, Nafea M. Fetal ECG Extraction Using Savitzky-Golay and Butterworth Filters. 2022 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) 2022. [DOI: 10.1109/i2cacis54679.2022.9815469] [Reference Citation Analysis]
3 Petmezas G, Stefanopoulos L, Kilintzis V, Tzavelis A, Rogers JA, Katsaggelos AK, Maglaveras N. State-of-the-art Deep Learning Methods on Electrocardiogram Data: A Systematic Review (Preprint).. [DOI: 10.2196/preprints.38454] [Reference Citation Analysis]
4 Petmezas G, Stefanopoulos L, Kilintzis V, Tzavelis A, Rogers JA, Katsaggelos AK, Maglaveras N. State-of-the-art Deep Learning Methods on Electrocardiogram Data: A Systematic Review (Preprint). JMIR Medical Informatics. [DOI: 10.2196/38454] [Reference Citation Analysis]
5 Brisk R, Bond RR, Finlay D, Mclaughlin JAD, Piadlo AJ, Mceneaney DJ. WaSP-ECG: A Wave Segmentation Pretraining Toolkit for Electrocardiogram Analysis. Front Physiol 2022;13:760000. [DOI: 10.3389/fphys.2022.760000] [Reference Citation Analysis]
6 Wakefield C, Yao L, Self S, Frasch MG. Wearable technology for health monitoring during pregnancy: an observational cross-sectional survey study.. [DOI: 10.1101/2022.01.26.22269158] [Reference Citation Analysis]