Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Classification and correlational analysis on lower spine parameters using data mining techniques Subject The topic of the resource Classification; Correlation; Data mining; Decision tree; Lower back pain; Pelvic incidence; Sacral slope; Spondylolisthesis; Support vector machines Description An account of the resource The application of data mining in the field of medical science is slowly gaining popularity. This is due to the fact that enormous statistical inferences from data related to the human body and medicine was a possible with high accuracy rates which was a tedious task in the past. This had led to discoveries and breakthroughs which has saved thousands of lives. Lower back pain is one of the most common issues faced by majority of the population throughout the world. The early detection and treatment of LBP can avoid life threatening issues in the body. Objective: This study aims to create a classification model which can be used to detect an unhealthy spine using the lumbar and sacral parameters. Correlational analysis was performed between different attributes to find distinguishing factors between healthy and unhealthy spine. Method: Classification methods were used such as decision tree and SVM. Correlational analysis was performed using pearson method between each attribute. Results: After creating the model using the different classification methods it was found that Ctree produced the highest accuracy with 92.80% on average. It was also found that there were 6 attribute pairs that had high correlation coefficient to distinguish unhealthy and healthy spine observations. BEIESP. Creator An entity primarily responsible for making the resource Johny R.V.; Roseline Mary R. Source A related resource from which the described resource is derived International Journal of Recent Technology and Engineering, Vol-7, No. 6, pp. 1450-1456. Publisher An entity responsible for making the resource available Blue Eyes Intelligence Engineering and Sciences Publication Date A point or period of time associated with an event in the lifecycle of the resource 2019-01-01 Identifier An unambiguous reference to the resource within a given context <a href="" target="_blank" rel="noreferrer noopener"></a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067055940&amp;partnerID=40&amp;md5=759470d8c842a716bfcc3197e783d299" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067055940&amp;partnerID=40&amp;md5=759470d8c842a716bfcc3197e783d299</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 22773878 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Johny R.V., Department of Computer Science, CHRIST (Deemed To Be University), India; Roseline Mary R., Department of Computer Science, CHRIST (Deemed To Be University), India