精神分裂症和双相情感障碍中的语义异常:一种自然语言处理方法
1Department of Psychiatry, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Gangdong-gu, South Korea.
Science progress
|January 23, 2025
概括
使用人工智能模型的语言分析揭示了精神分裂症和双相情感障碍患者之间的句子接受度和语义网络的显著差异,这可能有助于差异诊断.
科学领域:
- 精神病学是一个精神病学.
- 计算语言学 计算语言学
- 神经科学是一个神经科学.
背景情况:
- 由于症状重叠和鼻科的模糊性,精神分裂症和双相情感障碍之间的诊断区别仍然具有挑战性.
- 正式思维障碍在历史上一直是区分精神分裂症的关键特征,这表明语言改变可能至关重要.
- 研究语言作为一种潜在的生物标志物可以改进精神病学中的差异诊断.
研究的目的:
- 探索自然语言处理 (NLP) 在区分精神分裂症和双相情感障碍中的有用性.
- 在精神分裂症和双相情感障碍患者中识别明显的语言异常.
- 评估语言标记是否可以作为思维障碍的替代指标.
主要方法:
- 采用KoBERT和KoGPT语言模型来评估患者和对照组的句子可接受性.
- 为每个群体构建语义词汇网络以分析语言结构.
- 在患者组和对照组之间比较网络措施,包括平均聚类系数.
主要成果:
- 与对照组相比,精神分裂症和双相情感障碍组都表现出较低的句子接受度.
- 精神分裂症组表现出明显不那么可接受的句子比双相情感障碍组.
- 在精神分裂症和双相情感障碍之间的语义网络结构中观察到明显的差异,在大多数措施中,双相情感障碍处于精神分裂症和对照组之间.
结论:
- 在精神分裂症和双相情感障碍患者之间发现了句子接受度和语义网络指标的显著差异.
- 通过NLP识别的语言异常可以作为思维障碍的有价值的替代标记.
- 这些语言标记在改善精神分裂症和双相情感障碍之间的差异诊断方面表现有前途.
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