Open AccessPrediction of Parkinson’s Disease at Early Stage using Big Data Analytics
Author(s) -
Siva Sankara Reddy Donthi Reddy*,
Udaya Kumar Ramanadham
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.d8328.049420
Subject(s) - big data , predictive analytics , parkinson's disease , disease , data science , analytics , process (computing) , computer science , software analytics , affect (linguistics) , software , medicine , psychology , data mining , software development , pathology , software development process , communication , programming language , operating system
Due to technological improvements in healthcare industry and clinical medicine, it requires to adapt new software techniques and tools to predict, diagnose and analyze disease patterns for making decisions in the early stage of disease. Parkinson’s disease is a neurodegenerative disorder. The PD damage the motor skills and may create speech problem and also affect the decision making process. Many people suffers with PD all over the world from many years. Day by day, the PD data has been increased, so the existing data mining predictive methods and tools does not give accurate results early for making decisions by doctors to save and increase the patient life period. Early PD symptoms can be detected by Big Data Analytics and proper medicine will be provided at the right time. In this paper, we are doing survey of predictive methods, Big Data Analytical techniques and also earlier researchers results presented.