基于机器学习的抑郁症患者脑电图和诱发电位的人工智能分析

IF 0.9 Q4 TELECOMMUNICATIONS Internet Technology Letters Pub Date : 2023-05-05 DOI:10.1002/itl2.438
Jianqi Ma
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引用次数: 0

摘要

随着人们精神压力和生活节奏的不断提高,人们的学习和生活压力也会随之增大,从而导致人们抑郁症的增加。抑郁症是一种精神疾病,是一种与患者身体状况不相符的慢性精神疾病。近年来,随着人们对抑郁症的了解越来越多,对抑郁症的研究也越来越多,很多研究学者为抑郁症的治疗提供了新的思路,本文以此为研究方向和研究基础。本文介绍了脑电图(electroencephalogram,EEG)和诱发电位以及人工智能(Artificial intelligence,AI)方法的背景,然后基于人工智能对抑郁症患者进行分析,并总结了电子技术的应用。提出了抑郁症、脑电图和诱发电位的概念分析。文章最后,研究了机器学习在抑郁症中的应用。同时,随着机器学习在人工智能领域的不断发展,抑郁症患者脑电图和诱发电位相关工作也面临着新的机遇和挑战。
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Artificial intelligence analysis of electroencephalogram and evoked potential in patients with depression based on machine learning

With the continuous improvement of people's mental pressure and life pace, people's study and life pressure would increase, leading to the increase of people's depression. Depression is a mental illness, a chronic mental illness that is inconsistent with the patient's physical condition. In recent years, as people know more and more about depression, and they have more and more research on depression, many research scholars have provided new ideas for the treatment of depression, and this paper takes this as the research direction and research basis. This paper introduces the background of EEG (electroencephalogram, EEG) and evoked potential and artificial intelligence (Artificial intelligence, AI) methods, and then analyzes the patients with depression based on AI, and summarizes the application of electronics. The concept analysis of depression, EEG and evoked potential is put forward. At the end of the article, the application of machine learning in depression is studied. At the same time, with the continuous development of machine learning in artificial intelligence, the EEG and evoked potential related work in patients with depression are also facing new opportunities and challenges.

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