Prediction of Low Back Pain with Two Expert Systems

Sari M., GÜLBANDILAR E., Cimbiz A.

JOURNAL OF MEDICAL SYSTEMS, cilt.36, sa.3, ss.1523-1527, 2012 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 36 Sayı: 3
  • Basım Tarihi: 2012
  • Doi Numarası: 10.1007/s10916-010-9613-x
  • Dergi Adı: JOURNAL OF MEDICAL SYSTEMS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1523-1527
  • Anahtar Kelimeler: Low back pain, Artificial neural network (ANN), Adaptive neuro-fuzzy inference system (ANFIS), Modeling, Skin resistance, Expert system, Visual analog scale, ARTIFICIAL NEURAL NETWORKS, SKIN RESISTANCE METHOD, DECISION-SUPPORT, DIAGNOSIS
  • Eskişehir Osmangazi Üniversitesi Adresli: Evet

Özet

Low back pain (LBP) is one of the common problems encountered in medical applications. This paper proposes two expert systems (artificial neural network and adaptive neuro-fuzzy inference system) for the assessment of the LBP level objectively. The skin resistance and visual analog scale (VAS) values have been accepted as the input variables for the developed systems. The results showed that the expert systems behave very similar to real data and that use of the expert systems can be used to successfully diagnose the back pain intensity. The suggested systems were found to be advantageous approaches in addition to existing unbiased approaches. So far as the authors are aware, this is the first attempt of using the two expert systems achieving very good performance in a real application. In light of some of the limitations of this study, we also identify and discuss several areas that need continued investigation.