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Title : Deep learning-based Parkinsons Disease prediction using Recurrent Neural Networks
Author : KALWAKURTHI SRI SANDHYA, K BALAJI SUNIL CHANDRA, G BALA RENUKA
Biomarkers produced from human language may be used to study neurological illnesses like Parkinson's Disease (PD). About one million individuals are impacted by PD, a neurodegenerative illness that progresses over time. The severity of Parkinson's disease has been evaluated by doctors using subjective grading systems in the past. Finding and diagnosing Parkinson's disease via articulation is made feasible by difficulties in motor manipulation. Medical practitioners should reap the benefits of more affordable and precise diagnoses as a result of technology advancements and the widespread usage of sound storage devices in everyday life. utilising a decision-tree, logistic-regression, and Naive Bayes dataset as well as deep learning rule sets such Recurrent Neural Networks (RNN) for use predictions with pricing, we provide evidence to support this concept here utilising an audio dataset obtained from individuals with or without PD. Reliable and thorough evaluation of every
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Dr. Arend L Mapanawang, Sp.PD, FINASIM, PhD
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