Machine Learning Analysis of Electronic Nose in a Transdiagnostic Community Sample With a Streamlined Data Collection Approach: No Links Between Volatile Organic Compounds and Psychiatric Symptoms

Machine Learning Analysis of Electronic Nose in a Transdiagnostic Community Sample With a Streamlined Data Collection Approach: No Links Between Volatile Organic Compounds and Psychiatric Symptoms

Non-intrusive, easy-to-use and pragmatic collection of biological processes is warranted to evaluate potential biomarkers of psychiatric symptoms. Prior work with relatively modest sample sizes suggests that under highly-controlled sampling conditions, volatile organic compounds extracted from the h...

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Bibliographic Details
Main Authors: Bohan Xu, Mahdi Moradi, Rayus Kuplicki, Jennifer L. Stewart, Brett McKinney, Sandip Sen, Martin P. Paulus
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-09-01
Series:Frontiers in Psychiatry
Subjects:
machine learning
data mining
electronic nose
mental health
exhalomes
computational psychiatry
Online Access:https://www.frontiersin.org/article/10.3389/fpsyt.2020.503248/full

Internet

https://www.frontiersin.org/article/10.3389/fpsyt.2020.503248/full

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