A support vector machine model provides an accurate transcript-level-based diagnostic for major depressive disorder.

ABSTRACT: Major depressive disorder (MDD) is a critical cause of morbidity and disability with an economic cost of hundreds of billions of dollars each year, necessitating more effective treatment strategies and novel approaches to translational research. A notable barrier in addressing this public health threat involves reliable identification of the disorder, as many affected individuals remain undiagnosed or misdiagnosed. An objective blood-based diagnostic test using transcript levels of a panel of markers would provide an invaluable tool for MDD as the infrastructure-including equipment, trained personnel, billing, and governmental approval-for similar tests is well established in clinics worldwide. Here we present a supervised classification model utilizing support vector machines (SVMs) for t

SUBMITTER: Yu JS 

PROVIDER: S-EPMC5290347 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature