Use of pain-related gene features to predict depression by support vector machine model in patients with fibromyalgia.

ABSTRACT: The prevalence rate of depression is higher in patients with fibromyalgia syndrome, but this is often unrecognized in patients with chronic pain. Given that depression is a common major barrier in the management of patients with fibromyalgia syndrome, an objective tool that reliably predicts depression in patients with fibromyalgia syndrome could significantly enhance the diagnostic accuracy. Since pain and depression can cause each other and worsen each other, we wonder if pain-related genes can be used to differentiate between those with major depression from those without. This study developed a support vector machine model combined with principal component analysis to differentiate major depression in fibromyalgia syndrome patients using a microarray dataset, including 25 fibromyalgia

SUBMITTER: Wang F 

PROVIDER: S-EPMC10090498 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature