Parkinson’s Disease Detection And Classification Using Machine Learning And Deep Learning Algorithms– A Survey

Journal Title: International Journal of Engineering and Science Invention - Year 2018, Vol 7, Issue 5

Abstract

Parkinson's Disease Is A Neurodegenerative Ailment Which Influences Dopamine-Creating Neurons In Substantia Nigra, A Section Of The Brain. This Progressively Causes The Patients To Experience Issues In Talking, Strolling Or Finishing Other Basic Functions. The Recognition, Checking And Analysis Of Parkinson's Disease Have Been Enormously Affected By Speech Processing And Artificial Intelligence Strategies. Machine Learning And Deep Learning Algorithms Have Been Utilized Generally In The Determination Of Parkinson's Disease. Different Techniques That Are Utilized As A Part Of The Discovery, Grouping And Diagnosis Of Parkinson's Disease Have Been Contemplated In This Paper. The Features Extracted From The Voice Samples Of Patients Are Tested Utilizing Different Classification Models. The Significant Classification Models That Are Effectively Utilized Are Convolutional Neural Network (CNN), Support Vector Machine (SVM) And Artificial Neural Network (ANN). This Has Incredible Potential In Assisting The Doctors Amid Examination And Expanding The Medicinal Services Offices In The Territories Where Powerful Diagnosis Is Troublesome.

Authors and Affiliations

Muthumanickam S, Gayathri J, Eunice Daphne J

Keywords

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  • EP ID EP396740
  • DOI -
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How To Cite

Muthumanickam S, Gayathri J, Eunice Daphne J (2018). Parkinson’s Disease Detection And Classification Using Machine Learning And Deep Learning Algorithms– A Survey. International Journal of Engineering and Science Invention, 7(5), 56-63. https://europub.co.uk/articles/-A-396740