An interpretable deep-learning approach to detect biomarkers in anxious-depressed symptoms from prefrontal fNIRS signals during an autobiographical memory test.

Journal: Asian journal of psychiatry

PMID: 40158273

Abstract

BACKGROUND: Individuals with anxious-depressed (AD) symptoms have more severe mood disorders and cognitive impairment than those with non-anxious depression (NAD) symptoms. Therefore, it is important to clarify the underlying neurophysiology of these two symptom groups to optimize treatment.

Authors

Yan Zhang

Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, 110032, China.
Yawen Xu

Department of Urology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Yihang Cheng

Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, 510280, Guangdong, China.
Yihong Zhao

School of Nursing, Columbia University, New York, NY, United States.
Marc N Potenza

Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA.
Hui Shi

Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Keywords

Adult Anxiety Anxiety Disorders Biomarkers Deep Learning Depression Depressive Disorder Female Functional Neuroimaging Humans Male Memory, Episodic Middle Aged Prefrontal Cortex Sensitivity and Specificity Spectroscopy, Near-Infrared Young Adult

External Resources

View on PubMed Access via DOI PubMed (40158273)

An interpretable deep-learning approach to detect biomarkers in anxious-depressed symptoms from prefrontal fNIRS signals during an autobiographical memory test.

Abstract

Authors

Keywords

External Resources

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