DEEP CNN FOR PARKINSON'S DISEASE PREDICTION THROUGH IMAGE AND SPEECH DATA ANALYSIS

Authors

  • K. Ramadevi, Mekala Meghana, Nooneti Poojitha, Abbu Pavankalyan, Challa Ravi Teja

Keywords:

Keywords: Parkinson’s disease, deep learning, CNN, medical imaging, speech analysis, early diagnosis.

Abstract

Parkinson’s disease (PD) is a progressive neurodegenerative disorder marked by motor impairmentssuch as bradykinesia, tremors, and rigidity, caused by the loss of dopaminergic neurons. Early diagnosisis challenging due to the absence of a definitive test and reliance on subjective clinical evaluations. Thisstudy proposes an automated detection system using deep learning with multimodal data—brainimaging and speech recordings

References

U Haq, J. P. Li, B. L. Y. Agbley, C. B. Mawuli, Z. Ali, S. Nazir, S. U. Din, “A survey of deep learning techniques-based Parkinson’s disease recognition methods employing clinical data”, Expert Systems with Applications, Volume 208, 2022, 118045, ISSN 0957-4174,

https://doi.org/10.1016/j.eswa.2022.118045.

Clayton R. Pereira, Danilo R. Pereira, Gustavo H. Rosa, Victor H.C. Albuquerque, Silke A.T. Weber, Christian Hook, João P. Papa, Handwritten dynamics assessment through convolutional neural networks: An application to Parkinson's disease identification, Artificial Intelligence in Medicine, Volume 87, 2018, Pages 67-77, ISSN 0933-3657, https://doi.org/10.1016/j.artmed.2018.04.001.

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Published

2025-04-02

How to Cite

K. Ramadevi, Mekala Meghana, Nooneti Poojitha, Abbu Pavankalyan, Challa Ravi Teja. (2025). DEEP CNN FOR PARKINSON’S DISEASE PREDICTION THROUGH IMAGE AND SPEECH DATA ANALYSIS. Journal of Computational Analysis and Applications (JoCAAA), 34(4), 373–382. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/2308

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