A Survey of Predicting Parkinson’s & Atypical Parkinson Disease in the Primordial Stage by using Classification techniques in Data Mining

Authors

  • D.Karthiga Ph.D, Research scholar, Vivekanandha College of Arts and Sciences for Women (Autonomous) Elayampalayam,Namakkal (DT)-637205
  • Dr.P.Sumitra Assistant Professor,Dept of Computer Science, Vivekanandha College of Arts and Sciences for Women (Autonomous) Elayampalayam,Namakkal (DT)-637205

Keywords:

Progressive Supranuclear Palsy, Parkinson’s disease, Data Mining, atypical Parkinson disease and Classification

Abstract

Data mining has well known methods in extracting the information. Nowadays, people are not giving
prominent attention to their health. Most of the people find it difficult in diagnosing their condition by means of symptoms at
the exact time. Progressive Supranuclear Palsy (PSP) is a rare deteriorating neurological disorder that is often mispredicted
as Parkinson’s disease, because of its identical symptoms. There are many symptoms, that we can prognosis the neurological
disorder in the primordial stage. It is a challenging task to diagnose if a person is affected by PSP. The Data Mining
techniques are most significant in diagnosing & predicting the disease. This paper discusses the study of various data mining
methods in diagnosing the Parkinson and atypical Parkinson disease in the early stage to enhance the quality of living.

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Published

2018-02-25

How to Cite

D.Karthiga, & Dr.P.Sumitra. (2018). A Survey of Predicting Parkinson’s & Atypical Parkinson Disease in the Primordial Stage by using Classification techniques in Data Mining. International Journal of Advance Engineering and Research Development (IJAERD), 5(2), 794–797. Retrieved from https://ijaerd.org/index.php/IJAERD/article/view/2492

Issue

Vol. 5 No. 2 (2018): Volume 5 Issue 2 February 2018

Section

Articles