Diagnosis of Vertebral Column Disorders using A Novel Sprint Algorithm
K.N.Nithya1, P. Suresh2

1K.N.Nithya, PG and Research Department of Computer Science, Shri Sakthi Kailassh Women’s College Salem, Tamil Nadu India.
2Dr. P. Suresh, Head, Department of Computer Science, Salem Sowdeswari College , Salem Tamil Nadu India. 

Manuscript received on 01 August 2019. | Revised Manuscript received on 06 August 2019. | Manuscript published on 30 September 2019. | PP: 8920-8924 | Volume-8 Issue-3 September 2019 | Retrieval Number: C5630098319/2019©BEIESP | DOI: 10.35940/ijrte.C5630.098319

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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: Data mining in the medical field has witnessed huge popularity and their applications gained remarkable impact. In the past, disease diagnosis is considered as a tedious task because of the inaccuracy and time consumptions. This raises the necessity of a prominent disease analysis system which would save thousands of lives. To achieve this especially in data mining data mining is vital, its classification accuracy will be an efficient remedy for proper diagnosis of diseases. In the world, people are affected by various kinds of diseases, in which Lower back pain has gained attention in recent years. The main challenge is the detection of the healthy and unhealthy spine. In this paper, we proposed a SPRINT algorithm for achieving better classification results. The proposed concept is a key basis of Decision Tree which considers lumbar and sacral parameters that perform effectively on detecting unhealthy spines. The experimental result is carried out with three sets of datasets on WEKA, a perfect and popular data mining suite. The obtained results are compared with K-NN and rep-tree on the basis of several parameters. It is proven that on this comparison classification accuracy obtained by SPRINT algorithm is far better than k-nn and rep-tree thus ensuring its overall performance.
Keywords: Data Mining, Classification, Disease Diagnosis, and Lower Back Pain.

Scope of the Article: Classification