Open AccessDiagnosis of Parkinson’s Disorder through Speech Data using Machine Learning Algorithms
Author(s) -
Adlin Jebakumari S,
C.R. Chethan,
C. R. Aditya,
D Divitha,
Nagaraju T. R
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.c8060.019320
Subject(s) - parkinson's disease , machine learning , computer science , identification (biology) , disease , artificial intelligence , feature (linguistics) , feature extraction , algorithm , health care , medicine , pathology , linguistics , philosophy , botany , economics , biology , economic growth
Parkinson's disease is a neurodegenerative disorder that affects millions of people around the globe. Detecting Parkinson's disease at an earlier stage could help to better diagnose the disease. Machine learning provides potentially large opportunities for computer-aided identification and diagnosis that could minimize unavoidable health care errors and inherent clinical uncertainty, provide guidance, and improve decision-making. In this paper, we explore the feature extraction and prediction algorithms used to predict Parkinson's disease and provide a comprehensive comparison of these algorithms