About Dataset

Vertebral Column Data Set

Abstract

This dataset contains values for six biomechanical features used to classify orthopaedic patients into either:

Three classes: Normal, Disk Hernia, or Spondylolisthesis
Or two classes: Normal or Abnormal

Dataset Characteristics

Type: Multivariate
Attributes: Real-valued
Associated Tasks: Classification
Number of Instances: 310
Number of Attributes: 6
Missing Values: None
Date Donated: 2011-08-09

Source

Guilherme de Alencar Barreto (guilherme '@' deti.ufc.br)
Ajalmar Rêgo da Rocha Neto (ajalmar '@' ifce.edu.br)
Department of Teleinformatics Engineering, Federal University of Ceará, Fortaleza, Brazil

Henrique Antonio Fonseca da Mota Filho (hdamota '@' gmail.com)
Hospital Monte Klinikum, Fortaleza, Brazil

Data Set Information

The biomedical data was collected during a medical residency in the Group of Applied Research in Orthopaedics (GARO) at the Centre Médico-Chirurgical de Réadaptation des Massues in Lyon, France. The dataset supports two classification tasks:

Three-class classification:
- Normal – 100 patients
- Disk Hernia – 60 patients
- Spondylolisthesis – 150 patients
Binary classification:
- Normal – 100 patients
- Abnormal (Disk Hernia + Spondylolisthesis) – 210 patients

Files formatted for use in the WEKA machine learning environment are also provided.

Attribute Information

Each patient is described by six biomechanical attributes, derived from the shape and orientation of the pelvis and lumbar spine:

Pelvic incidence
Pelvic tilt
Lumbar lordosis angle
Sacral slope
Pelvic radius
Grade of spondylolisthesis

Class labels include:

DH – Disk Hernia
SL – Spondylolisthesis
NO – Normal
AB – Abnormal (binary classification)

Relevant Papers

Berthonnaud, E., Dimnet, J., Roussouly, P. & Labelle, H. (2005). “Analysis of the sagittal balance of the spine and pelvis using shape and orientation parameters.” Journal of Spinal Disorders & Techniques, 18(1):40–47.
Rocha Neto, A. R. & Barreto, G. A. (2009). “On the Application of Ensembles of Classifiers to the Diagnosis of Pathologies of the Vertebral Column: A Comparative Analysis.” IEEE Latin America Transactions, 7(4):487–496.
Rocha Neto, A. R., Sousa, R., Barreto, G. A. & Cardoso, J. S. (2011). “Diagnostic of Pathology on the Vertebral Column with Embedded Reject Option.” In Proceedings of the 5th Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA'2011), Lecture Notes on Computer Science, Vol. 6669, pp. 588–595.