A proof of concept machine learning analysis using multimodal neuroimaging and neurocognitive measures as predictive biomarker in bipolar disorder.

Journal: Asian journal of psychiatry
PMID: 32143176

Abstract

BACKGROUND: Concomitant use of complementary, multimodal imaging measures and neurocognitive measures is reported to have higher accuracy as a biomarker in Alzheimer's dementia. However, such an approach has not been examined to differentiate healthy individuals from Bipolar disorder. In this study, we examined the utility of support vector machine (SVM) technique to differentiate bipolar disorder patients and healthy using structural, functional and diffusion tensor images of brain and neurocognitive measures.

Authors

  • Rashmin Achalia
    Government Medical College, Aurangabad, India.
  • Anannya Sinha
    National Institute of Mental Health and Neurosciences, Bangalore, India.
  • Arpitha Jacob
    National Institute of Mental Health and Neurosciences, Bangalore, India.
  • Garimaa Achalia
    Achalia Neuropsychiatry Hospital, Aurangabad, Maharashtra, India.
  • Varsha Kaginalkar
    Government Medical College, Aurangabad, India.
  • Ganesan Venkatasubramanian
    National Institute of Mental Health and Neurosciences, Bangalore, India.
  • Naren P Rao
    Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore 560029, India. Electronic address: docnaren@gmail.com.

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