Comparative Analysis of Machine Learning Clustering Methods for Electroretinogram
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-62502-2_45
Reference21 articles.
1. Gupta, S.K., et al.: Electroretinogram responses in myopia: a review. Doc. Ophthalmol. 145(2), 77–95 (2021). https://doi.org/10.1007/s10633-021-09857-5
2. Hamilton, R.: Clinical electrophysiology of vision—commentary on current status and future prospects. Eye 35(9), 2341–2343 (2021). https://doi.org/10.1038/s41433-021-01592-0
3. Nezamabadi, K., Sardaripour, N., Haghi, B., Forouzanfar, M.: Unsupervised ECG analysis: a review. IEEE Rev. Biomed. Eng. 16, 208–224 (2023). https://doi.org/10.1109/rbme.2022.3154893
4. Hosseini, M.-P., Hosseini, A., Ahi, K.: A review on machine learning for EEG signal processing in bioengineering. IEEE Rev. Biomed. Eng. 14, 204–218 (2021). https://doi.org/10.1109/rbme.2020.2969915
5. Zhdanov, A., Dolganov, A., Borisov, V., Ronkin, M., Ponomarev, V., Zanca, D.: OculusGraphy: Ophthalmic electrophysiological signals database. IEEE Dataport (2022). https://doi.org/10.21227/r1wb-pg25
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