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Press Release

EEG is the Wave of the Future: Machine Learning Technology Highlighted in Biological Psychiatry Publication

MYnd Analytics
Posted on: 29 Sep 16

MISSION VIEJO, Calif., Sept. 27, 2016 (GLOBE NEWSWIRE) -- MYnd Analytics, Inc. (OTCQB:CNSOD) announces the publication of “Using Electroencephalography for Treatment Guidance in Major Depressive Disorder” in the journal Biological Psychiatry: Cognitive Neuroscience and Neuroimaging. The study is a review of the current literature on biomarkers derived from electroencephalography (EEG) and their role in guiding clinical treatment of major depression.  The publication highlights the opportunity for machine learning to deliver actionable information to mental health professionals: “The explosion of computational power over the last few decades has led to a dramatic increase in the use of computation-intensive methods to analyze large databases for biomedical research. … Machine learning offers an extraordinary opportunity to extract the most salient predictive features from large EEG datasets.”

One technology featured in the review is PEER, a predictive medicine technology developed by MYnd Analytics, Inc., which combines an EEG scan of brain function with a registry of over 38,000 outcomes for over 10,000 unique psychiatric patients. Outcomes are continually added to the Registry, making the guidance more predictive. Predictive accuracy increased from 86% to 91% as of the last update — clear demonstration of the PEER model.

Artificial Intelligence and Machine Learning are one of the hottest areas of healthcare, and mental health, in particular, can benefit from bringing evidence-based adjunctive information to guide treatment. George Carpenter, CEO of MYnd Analytics said: “Every patient deserves access to objective, evidence-based, personalized treatments.”

The full study, “Using Electroencephalography for Treatment Guidance in Major Depressive Disorder” has been published in Biological Psychiatry and can be read online.

The study’s authors are:

Elizabeth C. Wade, B.A., Clinical Research Coordinator, Icahn School of Medicine at Mount Sinai

Dan V. Iosifescu, M.D., MSc, Director, Adult Psychopharmacology Program, Associate Professor of Psychiatry and Neuroscience, Icahn School of Medicine at Mount Sinai

About MYnd Analytics, Inc.

MYnd Analytics, Inc. ( provides a unique set of reference data and analytic tools for clinicians and researchers in psychiatry. While treatment for mental disorders has doubled in the last 20 years, it is estimated that 17 million Americans have failed two or more medication therapies for their mental disorders. The Company’s Psychiatric EEG Evaluation Registry, or PEER Online, is a registry and reporting platform that allows medical professionals to exchange treatment outcome data for patients referenced to objective neurophysiology data obtained through a standard electroencephalogram (EEG).  Based on the Company’s original physician-developed database, there are now more than 38,000 outcomes for over 10,000 unique patients in the PEER registry.  The objective of PEER Online is to avoid trial and error pharmacotherapy, which is the dominant approach for treatment-resistant patients.

To read more about the benefits of this patented technology for patients, physicians and payers, please visit

Safe Harbor Statement Under the Private Securities Litigation Reform Act of 1995

Except for the historical information contained herein, the matters discussed are forward-looking statements made pursuant to the safe harbor provisions of the Private Securities Litigation Reform Act of 1995, as amended. These forward-looking statements involve risks and uncertainties as set forth in the Company's filings with the Securities and Exchange Commission. These risks and uncertainties could cause actual results to differ materially from any forward-looking statements made herein.


Media Contact: Lauren Jenkins ScoutComms (202) 596-5669

For more information:

Editor's Details

Mike Wood

Last updated on: 29/09/2016

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