• Users Online: 220
  • Print this page
  • Email this page
ORIGINAL ARTICLE
Year : 2016  |  Volume : 2  |  Issue : 3  |  Page : 82-86

Chronic pain challenge: A statistical machine-learning method for chronic pain assessment


1 Research Assistant, Department of Research and Development, Comprehensive Spine and Sports Center, Campbell, California, USA
2 Education Director, Department of Research and Development, Comprehensive Spine and Sports Center, Campbell, California, USA

Correspondence Address:
Aman Navani
Research Assistant Department of Research and Development, Comprehensive Spine and Sports Center, Campbell, California
USA
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.5005/jp-journals-10046-0048

Rights and Permissions

Aim: The objective of Chronic Pain Challenge project is designing and construction of a machine-learning system to calculate the dynamic changes to the chronic pain risk score of an individual based on various weighted health behaviors. Materials and methods: The visual analog scale (VAS) and Oswestry Disability Index (ODI) ratings of 218 subjects were studied for dynamic changes based on three weighted health behaviors, physical exercise, nutrition, and depression in order to predict their individual and cumulative impact on severity of chronic pain. The predictive function was used to produce confidence and prediction intervals for the calculation of new VAS and ODI scores using supervised and unsupervised machine-learning algorithms and R programing language for statistical computation. Results: This 9 months research study resulted in the development of innovative design and construction of a machinelearning program that accurately predicted the changes to standardized tests, such as VAS and ODI based on weighted values for depression score (DS), nutrition score (NS) and physical activity score (PAS). The testing of both extreme and moderate ranges of health behavior values in a variety of subjects and comparison against simple weightage confirmed the accuracy and validity of the program. Conclusion: Chronic Pain Challenge program is a valid and accurate method in predicting chronic pain risk of an individual based on the engagement in various health behaviors. The Chronic Pain Challenge program can predict and prevent progression of chronic pain and disability by global education and empowerment, thereby disrupting the current health care model with the emerging and accelerating technology. Clinical significance: The Chronic Pain Challenge program is an innovative statistical machine-learning program for chronic pain predictability based on individual's health behavior patterns.


[PDF]*
Print this article     Email this article
 Next article
 Previous article
 Table of Contents

 Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
 Citation Manager
 Access Statistics
 Reader Comments
 Email Alert *
 Add to My List *
 * Requires registration (Free)
 

 Article Access Statistics
    Viewed459    
    Printed26    
    Emailed0    
    PDF Downloaded66    
    Comments [Add]    
    Cited by others 2    

Recommend this journal