AI/ML

Machine-learning-based classification between post-traumatic stress disorder and major depressive disorder using P300 features.


Icon for Elsevier Science Icon for PubMed Central Related Articles

Machine-learning-based classification between post-traumatic stress disorder and major depressive disorder using P300 features.

Neuroimage Clin. 2019;24:102001

Authors: Shim M, Jin MJ, Im CH, Lee SH

Abstract
BACKGROUND: The development of optimal classification criteria for specific mental disorders which share similar symptoms is an important issue for precise diagnosis. We investigated whether P300 features in both sensor-level and source-level could be effectively used to classify post-traumatic stress disorder (PTSD) and major depressive disorder (MDD).
METHOD: EEG signals were recorded from fifty-one PTSD patients, 67 MDD patients, and 39 healthy controls (HCs) while performing an auditory oddball task. Amplitude and latency of P300 were evaluated, and the current source analysis of P300 components was conducted using sLORETA. Finally, we classified two groups using machine-learning methods with both sensor- and source-level features. Moreover, we checked the comorbidity effects using the same approaches (PTSD-mono diagnosis (PTSDm, n = 28) and PTSD-comorbid diagnosis (PTSDc, n = 23)).
RESULTS: PTSD showed significantly reduced P300 amplitudes and prolonged latency compared to HCs and MDD. Moreover, PTSD showed significantly reduced source activities, and the source activities were significantly correlated with symptoms of depression and anxiety. Also, the best classification accuracy at each pair was as follows: 80.00% (PTSD-HCs), 67.92% (MDD-HCs), 70.34% (PTSD-MDD), 82.09% (PTSDm-HCs), 71.58% (PTSDm-MDD), 82.56% (PTSDc-HCs), and 76.67% (PTSDc- MDD).
CONCLUSION: Since abnormal P300 reflects pathophysiological characteristics of PTSD, PTSD patients were well-discriminated from MDD and HCs when using P300 features. Thus, altered P300 characteristics in both sensor- and source-level may be useful biomarkers to diagnosis PTSD.

PMID: 31627171 [PubMed – indexed for MEDLINE]

Source link

Related posts

Health 2.0 Tackles The ‘Unacceptables’ of Healthcare

Newsemia

AHIMA Comments on ONC Request for Information on Certified EHR Reporting

Newsemia

ILTA Survey: 54% Of Firms ‘Not Pursuing AI/ML Options’ – And That’s Real Progress

Newsemia

This website uses cookies to improve your experience. We'll assume you're ok with this, but you can opt-out if you wish. Accept Read More

Privacy & Cookies Policy

COVID-19

COVID-19 (Coronavirus) is a new illness that is having a major effect on all businesses globally LIVE COVID-19 STATISTICS FOR World