抑郁症诊断：基于脑电图的认知生物标记和机器学习。

IF 2.6 3区心理学 Q2 BEHAVIORAL SCIENCES

Behavioural Brain Research Pub Date : 2024-11-06 DOI:10.1016/j.bbr.2024.115325

Kiran Boby, Sridevi Veerasingam

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引用次数: 0

摘要

抑郁症是一种复杂的精神疾病，对人和社会都有重大影响。本文研究了诊断抑郁症的传统技术以及新兴生物标志物（尤其是基于脑电图的生物标志物）的潜力。本综述探讨了认知生物标志物的意义，全面了解了它们在抑郁症整体评估中的作用。它还研究了抑郁症对不同脑区的影响，概述了未来有希望的研究领域，并强调了了解抑郁症神经生理学根源的重要性。此外，它还阐明了如何将机器学习和深度学习模型整合到基于脑电图的抑郁症诊断中，强调了它们在优化个性化治疗方案和提高脑电图数据分析诊断准确性方面的重要性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Depression diagnosis: EEG-based cognitive biomarkers and machine learning

Depression is a complex mental illness that has significant effects on people as well as society. The traditional techniques for the diagnosis of depression, along with the potential of nascent biomarkers especially EEG-based biomarkers, are studied. This review explores the significance of cognitive biomarkers, offering a comprehensive understanding of their role in the overall assessment of depression. It also investigates the effects of depression on various brain regions, outlines promising areas for future research, and emphasizes the importance of understanding the neurophysiological roots of depression. Furthermore, it elucidates how machine learning and deep learning models are integrated into EEG-based depression diagnosis, emphasizing their importance in optimizing personalized therapeutic protocols and improving diagnostic accuracy with EEG data analysis.

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来源期刊

Behavioural Brain Research 医学-行为科学

CiteScore

5.60

自引率

0.00%

发文量

383

审稿时长

61 days

期刊介绍： Behavioural Brain Research is an international, interdisciplinary journal dedicated to the publication of articles in the field of behavioural neuroscience, broadly defined. Contributions from the entire range of disciplines that comprise the neurosciences, behavioural sciences or cognitive sciences are appropriate, as long as the goal is to delineate the neural mechanisms underlying behaviour. Thus, studies may range from neurophysiological, neuroanatomical, neurochemical or neuropharmacological analysis of brain-behaviour relations, including the use of molecular genetic or behavioural genetic approaches, to studies that involve the use of brain imaging techniques, to neuroethological studies. Reports of original research, of major methodological advances, or of novel conceptual approaches are all encouraged. The journal will also consider critical reviews on selected topics.