Prediction of Parkinson’s Disease at Early Stage using Big Data Analytics 
Siva Sankara Reddy Donthi Reddy1, Udaya Kumar Ramanadham2
1Siva Sankara Reddy Donthi Reddy*, PhD scholar, Department of CSE, Bharath Institute of Higher Education and Research (BIHER), Chennai, Tamilanadu, India.
2Udaya Kumar Ramanadham, Professor, Department of Information Technology, Bharath Institute of Higher Education and Research (BIHER), Chennai, Tamilanadu, India.
Manuscript received on March 25, 2020. | Revised Manuscript received on April 26, 2020. | Manuscript published on April 30, 2020. | PP: 2453-2459 | Volume-9 Issue-4, April 2020. | Retrieval Number: D8328049420/2020©BEIESP | DOI: 10.35940/ijeat.D8328.049420
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Healthcare Industry, Clinical Medicine, Parkinson’s disease, Neurodegenerative, Big Data Analytics, Prediction.