AI Computing as Ubiquitous Healthcare Solution: Predict Parkinson's for Large Masses in Society

• Published in: IEEE transactions on computational social systems Vol. 10; no. 4; pp. 1 - 6
• Main Authors: Divyashree, P, Dwivedi, Priyanka
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.08.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 2-D CNN; Algorithms; Artificial intelligence; Artificial neural networks; Computation; Computational modeling; Data models; deep learning (DL); Diseases; gait impairment; Health care; Health services; Medical services; Neurological diseases; Parkinson's disease; Parkinson’s disease (PD); Predictive models; Two dimensional models
• ISSN: 2329-924X; 2329-924X; 2373-7476
• DOI: 10.1109/TCSS.2022.3224046

Parkinson's disease (PD) is one of the macroscale-effected neurological disorders that have adverse effects on the quality of life as they influence the proper functioning of organs. To misfortune, PD has limited diagnosing techniques and lacks treatment to cure at advanced stages. Therefore, there is a prime requirement to diagnose PD at the initial stage with the assistance of advanced technologies. This article focuses on the use of revolutionary computing technology, which is Artificial Intelligence (AI) to early diagnose this fatal disorder and provide an efficient healthcare solution. The compact Two-Dimensional Convolution Neural Network (2-D CNN)-based computing algorithm is developed to diagnose PD from the gait variation. The proposed system is able to provide promising accuracy of 98% in classifying PD that surpasses the current state-of-the-art performance. To provide a ubiquitous healthcare solution for diagnosing PD, the proposed 2-D CNN model will be a quantum leap breakthrough. Consequently, the progressive PD spread, growth, and severity can be efficiently controlled. Therefore, discern ubiquitous healthcare services for large masses in society.