Machine learning in major depression: From classification to treatment outcome prediction.

Journal: CNS neuroscience & therapeutics
Published Date: Aug 23, 2018

Abstract

AIMS: Major depression disorder (MDD) is the single greatest cause of disability and morbidity, and affects about 10% of the population worldwide. Currently, there are no clinically useful diagnostic biomarkers that are able to confirm a diagnosis of MDD from bipolar disorder (BD) in the early depressive episode. Therefore, exploring translational biomarkers of mood disorders based on machine learning is in pressing need, though it is challenging, but with great potential to improve our understanding of these disorders.

Authors

  • Shuang Gao
    School of Pharmacy, Shenyang Pharmaceutical University, Shenyang 110016, China.
  • Vince D Calhoun
    Mind Research Network & Lovelace Biomedical and Environmental Research Institute, Albuquerque, New Mexico; Department of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, New Mexico; Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, New Mexico; Department of Neurosciences, University of New Mexico, Albuquerque, New Mexico.
  • Jing Sui
    The Mind Research Network, Albuquerque, NM 87106, USA; Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

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