[HTML][HTML] Imperative role of machine learning algorithm for detection of Parkinson's disease: review, challenges and recommendations
Parkinson's disease (PD) is a neurodegenerative disease that affects the neural, behavioral,
and physiological systems of the brain. This disease is also known as tremor. The common …
and physiological systems of the brain. This disease is also known as tremor. The common …
[HTML][HTML] Applied machine learning techniques to diagnose voice-affecting conditions and disorders: Systematic literature review
Background Normal voice production depends on the synchronized cooperation of multiple
physiological systems, which makes the voice sensitive to changes. Any systematic …
physiological systems, which makes the voice sensitive to changes. Any systematic …
[HTML][HTML] Hybrid CNN-LSTM model with efficient hyperparameter tuning for prediction of Parkinson's disease
The patients' vocal Parkinson's disease (PD) changes could be identified early on, allowing
for management before physically incapacitating symptoms appear. In this work, static as …
for management before physically incapacitating symptoms appear. In this work, static as …
[HTML][HTML] Economics of artificial intelligence in healthcare: diagnosis vs. treatment
NN Khanna, MA Maindarkar, V Viswanathan… - Healthcare, 2022 - mdpi.com
Motivation: The price of medical treatment continues to rise due to (i) an increasing
population;(ii) an aging human growth;(iii) disease prevalence;(iv) a rise in the frequency of …
population;(ii) an aging human growth;(iii) disease prevalence;(iv) a rise in the frequency of …
[HTML][HTML] A Novel Artificial-Intelligence-Based Approach for Classification of Parkinson's Disease Using Complex and Large Vocal Features
Parkinson's disease (PD) affects a large proportion of elderly people. Symptoms include
tremors, slow movement, rigid muscles, and trouble speaking. With the aging of the …
tremors, slow movement, rigid muscles, and trouble speaking. With the aging of the …
End-to-end deep learning approach for Parkinson's disease detection from speech signals
C Quan, K Ren, Z Luo, Z Chen, Y Ling - Biocybernetics and Biomedical …, 2022 - Elsevier
More than 90% of patients with Parkinson's disease suffer from hypokinetic dysarthria. This
paper proposes a novel end-to-end deep learning model for Parkinson's disease detection …
paper proposes a novel end-to-end deep learning model for Parkinson's disease detection …
[HTML][HTML] Parkinson's disease detection using hybrid LSTM-GRU deep learning model
Parkinson's disease is the second-most common cause of death and disability as well as the
most prevalent neurological disorder. In the last 15 years, the number of cases of PD has …
most prevalent neurological disorder. In the last 15 years, the number of cases of PD has …
[HTML][HTML] A hybrid U-lossian deep learning network for screening and evaluating Parkinson's disease
R Maskeliūnas, R Damaševičius, A Kulikajevas… - Applied sciences, 2022 - mdpi.com
Speech impairment analysis and processing technologies have evolved substantially in
recent years, and the use of voice as a biomarker has gained popularity. We have …
recent years, and the use of voice as a biomarker has gained popularity. We have …
Parkinson's disease diagnosis using neural networks: Survey and comprehensive evaluation
Parkinson's disease (PD) is a chronic neurodegenerative disease of that predominantly
affects the elderly in today's world. For the diagnosis of the early stages of PD, effective and …
affects the elderly in today's world. For the diagnosis of the early stages of PD, effective and …
[HTML][HTML] The role of neural network for the detection of Parkinson's disease: a scoping review
MS Alzubaidi, U Shah, H Dhia Zubaydi, K Dolaat… - Healthcare, 2021 - mdpi.com
Background: Parkinson's Disease (PD) is a chronic neurodegenerative disorder that has
been ranked second after Alzheimer's disease worldwide. Early diagnosis of PD is crucial to …
been ranked second after Alzheimer's disease worldwide. Early diagnosis of PD is crucial to …