Advancements in Communication and Systems
Artificial Intelligence for Parkinson’s Disease Prediction
Authors: Soham Ravindran, Kaushal Kulkarni, Kaustubh Damle, Mousami Turuk and Manisha Sagade
Publishing Date: 20-01-2024
ISBN: 978-81-955020-7-3
Abstract
Parkinson’s disease (PD) is a pervasive neurodegenerative disorder with a diverse clinical presentation and a complex etiological landscape. A comprehensive introduction to the current state of PD research, diagnosis, and management, emphasizing the need for early detection and personalized treatment strategies is presented in this paper. Recognizing the multifactorial nature of PD, the genetic and environmental risk factors, highlighting the role of genetics in monogenic and polygenic PD are explored. Furthermore, the clinical diagnosis of PD, encompassing both motor and non-motor symptoms, and underscore the significance of a prolonged prodromal phase preceding clinical manifestations are discussed. The importance of personalized management, including pharmacological and non-pharmacological interventions, is also emphasized. In the quest for disease modification, the potential of emerging therapies and the ongoing research into the genetic basis of PD is explored. Notably, the promising role of machine learning techniques, including Convolutional Neural Networks (CNN), Artificial Neural Networks (ANN), KNearest Neighbors (KNN), and fuzzy logic, in early PD detection and diagnosis is investigated. By leveraging these advanced computational approaches, there is potential to revolutionize PD diagnosis, providing earlier interventions and tailored treatment strategies. This paper sets the stage for a comprehensive examination of the application of machine learning in PD research and clinical practice. By amalgamating existing knowledge and cutting-edge technologies, the aspiration of this paper is to advance the understanding and management of Parkinson’s disease, ultimately improving the lives of those affected by this challenging condition.
Keywords
SVM, KNN, ANN, Predictive analytics, Voice datasets, CNN, Fuzzy KNN, Fuzzy c-means
Cite as
Soham Ravindran, Kaushal Kulkarni, Kaustubh Damle, Mousami Turuk and Manisha Sagade, "Artificial Intelligence for Parkinson’s Disease Prediction", In: Ashish Kumar Tripathi and Vivek Shrivastava (eds), Advancements in Communication and Systems, SCRS, India, 2024, pp. 121-134. https://doi.org/10.56155/978-81-955020-7-3-11