Parkinson's disease diagnosis using neural networks: Survey and comprehensive evaluation

Abstract

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 powerful automated techniques are needed by recent enabling technologies as a tool. In this study, we present a comprehensive review of papers from 2013 to 2021 on the diagnosis of PD and its subtypes using artificial neural networks (ANNs) and deep neural networks (DNNs). We present detailed information and analysis regarding the usage of various modalities, datasets, architectures and experimental configurations in a succinct manner. We also present an in-depth comparative analysis of various proposed architectures. Finally, we present a number of relevant future directions for researchers in this area. © 2022 Elsevier Ltd