Literature DB >> 20978929

Prediction of low back pain with two expert systems.

Murat Sari1, Eyyup Gulbandilar, Ali Cimbiz.   

Abstract

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.

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Year:  2010        PMID: 20978929     DOI: 10.1007/s10916-010-9613-x

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  11 in total

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  6 in total

Review 1.  Artificial intelligence to improve back pain outcomes and lessons learnt from clinical classification approaches: three systematic reviews.

Authors:  Scott D Tagliaferri; Maia Angelova; Xiaohui Zhao; Patrick J Owen; Clint T Miller; Tim Wilkin; Daniel L Belavy
Journal:  NPJ Digit Med       Date:  2020-07-09

Review 2.  Developing and using expert systems and neural networks in medicine: a review on benefits and challenges.

Authors:  Abbas Sheikhtaheri; Farahnaz Sadoughi; Zahra Hashemi Dehaghi
Journal:  J Med Syst       Date:  2014-07-16       Impact factor: 4.460

Review 3.  Artificial Intelligence and Computer Aided Diagnosis in Chronic Low Back Pain: A Systematic Review.

Authors:  Federico D'Antoni; Fabrizio Russo; Luca Ambrosio; Luca Bacco; Luca Vollero; Gianluca Vadalà; Mario Merone; Rocco Papalia; Vincenzo Denaro
Journal:  Int J Environ Res Public Health       Date:  2022-05-14       Impact factor: 4.614

4.  Opioid prescribing by physicians with and without electronic health records.

Authors:  Christopher A Harle; Robert L Cook; Heidi S Kinsell; Jeffrey S Harman
Journal:  J Med Syst       Date:  2014-10-10       Impact factor: 4.460

Review 5.  Artificial intelligence to improve back pain outcomes and lessons learnt from clinical classification approaches: three systematic reviews.

Authors:  Scott D Tagliaferri; Maia Angelova; Xiaohui Zhao; Patrick J Owen; Clint T Miller; Tim Wilkin; Daniel L Belavy
Journal:  NPJ Digit Med       Date:  2020-07-09

6.  A Review on the Use of Artificial Intelligence in Spinal Diseases.

Authors:  Parisa Azimi; Taravat Yazdanian; Edward C Benzel; Hossein Nayeb Aghaei; Shirzad Azhari; Sohrab Sadeghi; Ali Montazeri
Journal:  Asian Spine J       Date:  2020-04-24
  6 in total

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