基于机器学习和文本挖掘的抑郁症的亚型和传统中医治疗研究
Fan Mengyue1, Yao Lin1, Zhang Guoqing2
1Innovation Research Institute of Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250355, China.
Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan
|September 28, 2025
概括
人工智能 (AI) 和机器学习从传统中医 (TCM) 文献中确定了9种抑郁症亚型. 每个亚型都有不同的处方,其中一个与调治疗相关.
科学领域:
- 综合医学是一个整体的医学.
- 计算生物学 计算生物学
- 药理学 药理学是指药理学的学科.
背景情况:
- 抑郁症的诊断和治疗仍然是复杂的挑战.
- 传统中医 (TCM) 提供了广泛的经验数据来管理抑郁症.
- 整合人工智能与TCM可以解锁对抑郁症亚型和治疗的新见解.
研究的目的:
- 利用人工智能 (AI) 根据传统中医 (TCM) 的原则来分类抑郁症.
- 为每个已识别的抑郁症亚型确定特定的TCM治疗策略.
- 用人工智能分析广泛的TCM文献,以加强抑郁症研究.
主要方法:
- 从3522个TCM文献来源中提取了抑郁症的症状,征兆和处方.
- 使用医学主题标题 (MeSH) 来建立症状/迹象之间的等级关系.
- 开发了一个无监督的机器学习集群模型,以将抑郁症患者分类为亚型.
- 对每个抑郁症群集分析了药物规则并确定了治疗模式.
主要成果:
- 创建了一个全面的MySQL数据库的抑郁症状/迹象和相关的TCM草药.
- 通过无监督集群分析揭示了9种不同的抑郁症亚型.
- 为每个抑郁症亚型建立了一个独特的TCM治疗处方.
- 确定了一种特定的亚型,该亚型始终使用 Qi 调色配方治疗,并得到了 Qi 缺乏症患者数据的支持.
结论:
- 机器学习和文本挖掘成功地确定了抑郁症亚型及其相应的TCM治疗方法.
- 这种人工智能驱动的方法为基于TCM的个性化抑郁症治疗提供了数据驱动的基础.
- 这项研究强调了人工智能在解读传统医疗系统中的复杂模式方面的潜力.
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