Early Diagnosis of Parkinson’s Disease Using LSTM: A Deep Learning Approach
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-73689-7_44
Reference17 articles.
1. Pearce, J.M.S.: Aspects of the history of Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry (1989). https://doi.org/10.1136/jnnp.52.Suppl.6
2. Challa, K.N.R., Pagolu, V.S., Panda, G., Majhi, B.: An improved approach for prediction of Parkinson’s disease using machine learning techniques. In: International Conference on Signal Processing, Communication, Power and Embedded System, SCOPES 2016, Proceedings, pp. 1446–1451 (2017). https://doi.org/10.1109/SCOPES.2016.7955679
3. Senturk, Z.K.: Early diagnosis of Parkinson’s disease using machine learning algorithms. Med. Hypotheses 138, 109603 (2020). https://doi.org/10.1016/j.mehy.2020.109603
4. Chan, D.K.Y., Hung, W.T., Wong, A., Hu, E., Beran, R.G.: Validating a screening questionnaire for parkinsonism in Australia. J. Neurol. Neurosurg. Psychiatry 69(1), 117–120 (2000). https://doi.org/10.1136/jnnp.69.1.117
5. Challa, K.N.R., Pagolu, V.S., Panda, G., Majhi, B.: An improved approach for prediction of Parkinson’s disease using machine learning techniques. In: International Conference on Signal Processing, Communication, Power and Embedded System, SCOPES 2016 - Proceedings, pp. 1446–1451 (2017). https://doi.org/10.1109/SCOPES.2016.7955679
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