Comparative Analysis for Feature Selection Approaches for Parkinson’s Disease Prediction
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Publisher
Springer Nature Switzerland
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https://link.springer.com/content/pdf/10.1007/978-3-031-64813-7_21
Reference10 articles.
1. Vigneswari, D.A., Aravinth, J.: Parkinson's disease Diagnosis using Voice Signals by Machine Learning Approach. In: 2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT), pp. 869–872. Bangalore, India (2021). https://doi.org/10.1109/RTEICT52294.2021.9573689
2. Fadil, R., et al.: 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). Mexico 2021, 2433–2436 (2021). https://doi.org/10.1109/EMBC46164.2021.9630451
3. R, N.D.., S, V. A, A.R., E, A., G, S.: Detecting Parkinson's Disease using Machine Learning. In: 2023 International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent Engineering (ICECONF), pp. 1–6. Chennai, India (2023). https://doi.org/10.1109/ICECONF57129.2023.10083581
4. Igene, L., Alim, A., Imtiaz, M.H., Schuckers, S.: A machine learning model for early prediction of parkinson's disease from wearable sensors. In: 2023 IEEE 13th Annual Computing and Communication Workshop and Conference (CCWC), pp. 0734–0737. Las Vegas, NV, USA (2023). https://doi.org/10.1109/CCWC57344.2023.10099230
5. S, S., S, A., Rao, G.V.V., Mohanraj, P.V.K., Azhagumurugan, R.: Parkinson's Disease Prediction Using Machine Learning Algorithm. In: 2022 International Conference on Power, Energy, Control and Transmission Systems (ICPECTS), pp. 1–5. Chennai, India (2022). https://doi.org/10.1109/ICPECTS56089.2022.10047447
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