摘要
抑郁症是以显著而持久的情感或心境低落为主要特征的一组疾病,给家庭和社会带来沉重的负担.但目前抑郁症的早期识别、诊断、鉴别诊断及治疗等方面常受困于客观指标的缺乏.近年来,人工智能技术开始逐渐应用于抑郁症的临床诊治和管理中,为抑郁症的诊治提供了更加客观和高效的方法.人工智能技术结合量表、生理指标可提高抑郁症的诊断正确率,基于神经影像、外周生物学标志、多模态的人工智能技术对抑郁症和双相抑郁鉴别具有价值,人工智能技术还可应用于抑郁症的药物、心理、物理治疗,以及健康管理和早期预测.本文旨在为人工智能技术更好地应用于抑郁症临床管理提供新的思路和依据.
Abstract
Depression is a group of diseases characterized by significant and persistent emotional or mental depression,which imposes a heavy burden on families and society. However,the early identification,diagnosis,differential diagnosis,and treatment of depression are often hindered by the lack of objective indicators. In recent years,artificial intelligence (AI) technology has gradually been applied in the clinical diagnosis,treatment,and management of depression,providing a more objective and efficient method for the diagnosis and treatment of depression. The integration of AI technology with rating scales and physiological indicators can enhance the diagnostic accuracy of depression. AI technology,based on neuroimaging,peripheral biomarkers,and multimodal approaches,holds value in distinguishing depression from bipolar depression. Additionally,AI technology can be applied to pharmacological,psychological,and physical treatments for depression,as well as to health management and early prediction. This article aims to provide new insights and evidence for the better application of AI technology in the clinical management of depression.
维普
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