EconPapers    
Economics at your fingertips  
 

A novel fractional Parkinson's disease onset model involving α-syn neuronal transportation and aggregation: A treatise on machine predictive networks

Roshana Mukhtar, Chuan-Yu Chang, Aqib Mukhtar, Muhammad Junaid Ali Asif Raja, Naveed Ishtiaq Chaudhary, Zeshan Aslam Khan and Muhammad Asif Zahoor Raja

Chaos, Solitons & Fractals, 2025, vol. 194, issue C

Abstract: Artificial intelligence plays a crucial role in medical care by enhancing diagnostic accuracy, personalizing treatment plans, and streamlining administrative processes, ultimately improving patient outcomes and operational efficiency. Additionally, it aids in predictive analytics, helping to identify potential health issues before they become critical. This paper presents a novel fractional mathematical model for α-syn transport and aggregation in neurons leading to the onset of Parkinson's disease (α-syn-TAN-OPD). A Nonlinear Autoregressive Exogenous (input) Neural Network optimized with Levenberg Marquardt Backpropagation technique (NARX-NN-LMBT) is expertly deployed on the fractional α-syn-TAN-OPD model. Fractional Adams-Bashforth-Moulton numerical scheme is deployed to generate three scenarios with five different fractional order cases each by varying α-syn synthesis rate, monomeric α-syn concentration decay, and misfolded α-syn production rate. These synthetic datasets are passed to the NARX-NN-LMBT to simulate, model, and anticipate the α-syn-TAN-OPD scenarios. The NARX-NN-LMBT technique is validated using mean squared error (MSE), root MSE, normalized MSE and mean absolute error performance evaluations. Graphical descriptions of regression indices, error-input cross correlation, error autocorrelation, error histograms further detail the prowess of the NARX-NN-LMBT technique for the accurate modeling of α-syn-TAN-OPD cases. A comparative analysis is drawn between the numerical scheme and the NARX-NN-LMBT with mean absolute error lying between the ranges of 10−7 to 10−8. NARX-NN-LMBT forecasting ability is assessed on single and multiple steps with the MSE lying in the range of 10−13 to 10−16.

Keywords: Artificial intelligence; α-Syn transport and aggregation in neurons leading to Parkinson's disease; Neural network; Levenberg Marquardt; Fractional Adams-Bashforth-Moulton numerical scheme (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077925002826
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:194:y:2025:i:c:s0960077925002826

DOI: 10.1016/j.chaos.2025.116269

Access Statistics for this article

Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros

More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().

 
Page updated 2025-04-08
Handle: RePEc:eee:chsofr:v:194:y:2025:i:c:s0960077925002826