Applying Deep Learning for the Examination of Voice Disorders in the Identification of Parkinson's Disease

Kushagra Gupta, Vedant Jain, J. Andrew

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Parkinson's disease is a degenerative neurological condition marked by difficulties with coordination, tremors, and rigidity in the muscles. Positively, speech recordings show potential as a precocious biomarker for Parkinson's disease, able to identify minute alterations prior to the manifestation of other symptoms. The main objective of this research is to create a machine learning model that can analyse speech recordings and reliably determine whether Parkinson's disease is present. Key questions that the model aims to answer include how well it detects early signs of Parkinson's disease, how well it distinguishes between voice samples from healthy individuals and those from early stages of Parkinson's disease, and whether or not accuracy will vary depending on variables like the length or calibre of voice recordings. The primary goal is to use deep learning methods to analyse voice data to detect Parkinson's disease early on.

Original languageEnglish
Title of host publicationInternational Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023
EditorsSuman Kumar Swarnkar, Yogesh Kumar Rathore
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350330915
DOIs
Publication statusPublished - 2023
Event1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023 - Raipur, India
Duration: 29-12-202330-12-2023

Publication series

NameInternational Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023

Conference

Conference1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023
Country/TerritoryIndia
CityRaipur
Period29-12-2330-12-23

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Media Technology
  • Health Informatics
  • Management of Technology and Innovation
  • Artificial Intelligence
  • Health(social science)

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