Data mining: comparing the empiric CFS to the Canadian ME/CFS case definition

作者：Jason Leonard A^*; Skendrovic Beth; Furst Jacob; Brown Abigail; Weng Angela; Bronikowski Christine

来源：Journal of Clinical Psychology, 2012, 68(1): 41-49.

DOI：10.1002/jclp.20827

• chronic fatigue syndrome
• myalgic encephalomyelitis
• data mining
• empiric CFS case definition
• Canadian clinical ME
• CFS case definition

This article contrasts two case definitions for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). We compared the empiric CFS case definition (Reeves et al., 2005) and the Canadian ME/CFS clinical case definition (Carruthers et al., 2003) with a sample of individuals with CFS versus those without. Data mining with decision trees was used to identify the best items to identify patients with CFS. Data mining is a statistical technique that was used to help determine which of the survey questions were most effective for accurately classifying cases. The empiric criteria identified about 79% of patients with CFS and the Canadian criteria identified 87% of patients. Items identified by the Canadian criteria had more construct validity. The implications of these findings are discussed.

• 出版日期2012-1
• 单位西北大学