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PARKINSONNET: CLASSIFICATION PARKINSON'S DISEASE MODEL BASED ON NOVEL DEEP LEARNING STRUCTURE

Year 2023, Volume: 7 Issue: 2, 259 - 276, 31.12.2023
https://doi.org/10.53600/ajesa.1382806

Abstract

Over the last few decades, neuroimaging, particularly magnetic resonance imaging (MRI), has played a significant sessional part in studying brain functions and diseases. MRI images, combined with unique ML approaches and developed tools during these years, have opened up new opportunities for diagnosing neurological illnesses. However, due to the apparent symptoms that are similar to each other, brain illnesses are regarded as difficult to precisely detect. This research examines a newly developed algorithm (ParkinsonNet) to classify Parkinson's disorder into two unique classes which are Control (healthy) and Parkinson's (PD), this method is one of the deep learning approaches, Convolutional neural networks (CNN). CNN is one way that may be used to classify a range of brain illnesses such as Parkinson's. We employed a freshly constructed CNN technique from scratch, and we got 97.9% accuracy which is considered outstanding compared with recently published articles using the same dataset

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Year 2023, Volume: 7 Issue: 2, 259 - 276, 31.12.2023
https://doi.org/10.53600/ajesa.1382806

Abstract

References

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  • Dai, Yin, Zheng Tang, and Yang Wang. 2019. 'Data driven intelligent diagnostics for Parkinson’s disease', IEEE Access , 7: 106941 50. Danielyan, Arman, and Henry A Nasrallah. 2009. 'Neurological disorders in schizophrenia', Psychiatric Clinics , 32: 719 57.
  • Diaz, Moises, Miguel Angel Ferrer, Donato Impedovo, Giuseppe Pirlo, and Gennaro Vessio. 2019. 'Dynamically enhanced static handwriting representation for Parkinson’s disease detection', Pattern Recognition Letters , 128: 204 10.
  • Diaz, Moises, Momina Moetesum, Imran Siddiqi, and Gennaro Vessio. 2021. 'Sequence based dynamic handwriting analysis for Parkinson’s disease detection with one dimensional convolutions and BiGRUs', Expert Systems with Applications , 168:
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There are 86 citations in total.

Details

Primary Language English
Subjects Software Engineering (Other), Biomaterials in Biomedical Engineering, Biomechanical Engineering
Journal Section Research Article
Authors

Saif Al-jumaili 0000-0001-7249-4976

Publication Date December 31, 2023
Submission Date October 31, 2023
Acceptance Date November 1, 2023
Published in Issue Year 2023 Volume: 7 Issue: 2

Cite

APA Al-jumaili, S. (2023). PARKINSONNET: CLASSIFICATION PARKINSON’S DISEASE MODEL BASED ON NOVEL DEEP LEARNING STRUCTURE. AURUM Journal of Engineering Systems and Architecture, 7(2), 259-276. https://doi.org/10.53600/ajesa.1382806