Diagnosing Parkinson's Disease from Voice Using Random Forest and Conversion in TensorFlow Lite

Machine learning system for Parkinson's diagnosis through voice analysis with 92% accuracy, converted to TensorFlow Lite for mobile deployment.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-07-12
DOI
https://doi.org/10.5281/zenodo.15870120
Primary Topic
Voice and Speech Disorders
Type
article
Field-Weighted Citation Impact
0.00
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article

Diagnosing Parkinson's Disease from Voice Using Random Forest and Conversion in TensorFlow Lite

Zenodo (CERN European Organization for Nuclear Research)
Voice and Speech Disorders
article

Diagnosing Parkinson's Disease from Voice Using Random Forest and Conversion in TensorFlow Lite

article en

Abstract

Machine learning system for Parkinson's diagnosis through voice analysis with 92% accuracy, converted to TensorFlow Lite for mobile deployment.

Zenodo (CERN European Organization for Nuclear Research)
ICE Publishing (GB)
Openalex Percentile: Top 49%
Voice and Speech Disorders
DOIOpen Access PDFOpenAlex
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Diagnosing Parkinson's Disease from Voice Using Random Forest and Conversion in TensorFlow Lite · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS