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一个新的基于人工智能的临床决策支持系统,用于诊断基于语音分析的严重精神疾病

Neslihan Cansel¹, Ömer Faruk Alcin², Ömer Furkan Yılmaz³

¹Assoc. Prof. Dr., Department of Psychiatry, Inonu University, Faculty of Medicine, Malatya, Turkey.

Psychiatria Danubina

|November 22, 2023

概括

人工智能可以使用语音分析准确检测精神疾病. 这种人工智能模型在区分双相,抑郁,焦虑和精神分裂症谱系障碍方面取得了96.94%的成功率.

科学领域:

精神病学是一个精神病学.
人工智能的人工智能
语音信号处理语音信号处理

背景情况:

语音特征对于精神病的心理评估和监测至关重要.
这项研究的重点是利用语音信号来识别精神疾病.

研究的目的:

开发基于人工智能的临床决策支持系统.
使用语音信号来区分双相,抑郁,焦虑和精神分裂症谱系障碍.

主要方法:

79名患者 (15名精神分裂症患者,24名焦虑症患者,25名抑郁症患者,15名双相情感患者) 和25名健康对照参与了这项研究.
使用波形包转换 (WPT),Mel频率角质系数 (MFCC) 和Gammatone角质系数 (GTCC) 分析了语音信号.
用分类器k-最近邻居 (kNN) 和支持矢量机器 (SVM) 来进行疾病分类.

主要成果:

开发的AI模型在区分精神疾病方面取得了96.94%的成功率.
kNN在诊断双相情感障碍方面表现出色,但对抑郁症的治疗效果不佳.
SVM对焦虑和精神病的准确性很高,但对双相情感障碍的准确性较低.

结论:

语音分析是区分主要精神疾病的一种可行的方法.
人工智能驱动的系统具有显著的潜力,可以提高精神病诊断的准确性和效率.

关键词:

人工智能的人工智能是人工智能.拉塞尔的情感模型精神疾病精神疾病精神病学是一种精神病学.语音信号语音信号的使用

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