2021
DOI: 10.3390/healthcare9060740
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The Role of Neural Network for the Detection of Parkinson’s Disease: A Scoping Review

Abstract: 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 combat against PD to allow patients to deal with it properly. However, there is no medical test(s) available to diagnose PD conclusively. Therefore, computer-aided diagnosis (CAD) systems offered a better solution to make the necessary data-driven decisions and assist the physician. Numerous studies were conducted to propose CAD to dia… Show more

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Cited by 46 publications
(25 citation statements)
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References 104 publications
(161 reference statements)
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“…The research articles selected for the studies consist of various parameters like detections of the PD by using machine learning, deep learning, hybrid learning, and AI. These research articles have also shown the classification of the normal vs. PD-affected people, the demographic analysis of the PD-affected patients, and the classification of the PD by considering the input parameter alternative assessment as one method to detect PD [ 9 ]. Studies unrelated to the symptomatic observation of PD are eliminated in published papers for many reasons [ 11 , 12 , 38 ].…”
Section: Search Strategy and Statistical Distributionmentioning
confidence: 99%
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“…The research articles selected for the studies consist of various parameters like detections of the PD by using machine learning, deep learning, hybrid learning, and AI. These research articles have also shown the classification of the normal vs. PD-affected people, the demographic analysis of the PD-affected patients, and the classification of the PD by considering the input parameter alternative assessment as one method to detect PD [ 9 ]. Studies unrelated to the symptomatic observation of PD are eliminated in published papers for many reasons [ 11 , 12 , 38 ].…”
Section: Search Strategy and Statistical Distributionmentioning
confidence: 99%
“…It is seen that many of the AI models show high accuracy, but the data size used for the testing and training of the algorithm is small, and the model fails to explain scientific validation. Hence, it results in High-Moderate (HM) in the studies [ 1 , 5 , 9 , 37 , 62 , 65 ]. The cumulative cutoff for the studies was determined by using various factors such as (i) associated studies of the PD, (ii) impact factor, (iii) the selected data, (iv) performance indicators, (v) clinical trials, etc.…”
Section: Ranking Of Selected Studiesmentioning
confidence: 99%
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