基于脑功能连接探讨机器学习在针刺治疗失眠效果预测中的应用
尹雪娇1 姜同菲1 陈昭伊1 宋章筱2 李彬1 郭静1
1.首都医科大学附属北京中医医院针灸中心/针灸神经调控北京市重点实验室,北京 100010;
2.北京中医药大学临床医学院,北京 100105
Exploring the application of machine learning in predicting the effect of acupuncture for insomnia based on brain functional connectivity
YIN Xuejiao1 JIANG Tongfei1 CHEN Zhaoyi1 SONG Zhangxiao2 LI Bin1 GUO Jing1
1.Department of Acupuncture and Moxibustion, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing Key Laboratory of Acupuncture Neuromodulation, Beijing 100010, China;
2.School of Clinical Medicine, Beijing University of Chinese Medicine, Beijing 100105, China
摘要 针灸是治疗失眠的有效途径之一,但因基于临床经验,治疗方案尚待优化,且效果以主观评测为主,个体效果差异明显。因此,筛选有效人群的个体识别标记,预测疗效,优化针刺治疗方案十分重要。机器学习技术(ML)的分类和预测算法正迅速成为疾病诊断、预测及分类工具。而磁共振成像技术已揭示失眠个体的脑功能连接(FC)具有高度特异性,在针刺前后有特定的变化规律,可作为追踪治疗反应的标志物。本文拟基于FC技术,探析运用ML中的分类算法模型预测针刺治疗失眠疗效的可行性,为突破“经验治疗”瓶颈、优化针刺治疗方案提供借鉴。
关键词 :
机器学习 ,
脑功能连接 ,
失眠 ,
针刺 ,
效果预测
Abstract :Acupuncture is one of the effective ways to treat insomnia, but because it is based on clinical experience, the treatment protocol has yet to be optimized, and the efficacy is mainly subjective assessment, with significant differences in individual efficacy. Therefore, it is important to screen effective populations for individual identification markers to predict efficacy and optimize acupuncture treatment protocols. Machine learning (ML) for classification and prediction algorithms are rapidly becoming tools for disease diagnosis, prediction, and classification. In contrast, magnetic resonance imaging has revealed that the brain functional connectivity (FC) of insomniac individuals is highly specific, with specific patterns of change before and after acupuncture, and can be used as a marker to track treatment response. This paper proposes to explore the feasibility of using the classification algorithm model in ML to predict the efficacy of acupuncture treatment for insomnia based on FC technology, in order to break the bottleneck of “empirical treatment” and optimize the acupuncture treatment plan.
Key words :
Machine learning
Brain functional connectivity
Insomnia
Acupuncture
Efficacy prediction
基金资助: 北京市自然科学基金面上项目(7212170);
国家自然科学基金面上项目(81774391)。
通讯作者:
郭静(1970-),女,博士,主任医师,教授,博士生导师;研究方向:脑病针刺临床及机制研究。
作者简介 : 尹雪娇(1997-),女,首都医科大学中医药临床学院2021级针灸学专业在读硕士研究生;研究方向:针刺治疗失眠的临床研究。
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