基于深度学习情感分类模型的个性化抑郁症护理策略  

Individualized depression nursing strategy based on deep learning emotion classification models

作　　者：袁丽洁[1] 武卓[2] 李敏[3] 雷涛[4] 祝婷[5] Yuan Lijie;Wu Zhuo;Li Min;Lei Tao;Zhu Ting(Department of Medical Office Infection Management,Shaanxi Provincial People′s Hospital,Xi′an 710068,China)

机构地区：[1]陕西省人民医院医务处感染管理科,陕西西安710068 [2]陕西省人民医院医学装备部,陕西西安710068 [3]陕西省人民医院保健办,陕西西安710068 [4]陕西科技大学电子信息与人工智能学院 [5]陕西省人民医院神经内科,陕西西安710068

出　　处：《护理学杂志》2020年第22期85-88,共4页Journal of Nursing Science

基　　金：国家自然科学基金项目(61461025)。

摘　　要：目的探讨人工智能技术在个性化抑郁症护理中的应用,实现精准护理以加速抑郁症患者的康复。方法将60例抑郁症患者按病种和病情分层随机分配为对照组和观察组各30例.对照组采用传统护理方法;观察组采用基于深度学习情感分类模型分类后的个性化护理方案,即利用脑电图像(EEG)采集设备获取大量带标记的脑电信号数据构建EEG情感训练库,标记抑郁症类型;通过深度学习情感分类模型识别抑郁症患者EEG信号对应的情感类别;根据其识别结果,采取相应的个性化护理措施。对两组患者在住院期间进行等间隔的抑郁量化评估和护理满意率调查。结果干预4周时,观察组汉密尔顿抑郁量表(HAMD)和自评抑郁量表(SDS)的评分显著低于对照组(均P<0.05);观察组干预8周时的康复率高于对照组,但两组比较,差异无统计学意义(P>0.05)。结论基于深度学习情感分类模型的个性化护理方法能显著缓减患者的抑郁程度,加快抑郁症患者的康复速度。Objective To explore the application of artificial intelligence technology in individualized depression care for patients with depression,to achieve precise care goal,and to accelerate the rehabilitation of them.Methods Totally,60 patients with depression were evenly and randomly assigned to a control group and an intervention group in the study.The control group received traditional nursing,while the intervention group received individualized nursing care based on deep learning emotion classification models:firstly,EEG data with labels were captured by electronic devices;secondly,the emotion classification model based on deep learning was used to recognize the real emotion of patients;thirdly,individualized nursing strategy was selected according to the recognized result.Quantitative assessment of depression and nursing satisfaction of patients in both groups during hospitalization were investigated.Results Four weeks into the intervention,the intervention group had significantly lower HAMD scores and SDS scores than the controls(P<0.05 for both).Eight weeks into the intervention,the intervention group had higher recovery rate,though the difference between the 2 groups was not significant(P>0.05).Conclusion Individualized depression nursing strategy based on deep learning emotion classification models can significantly relieve the degree of depression and accelerate the recovery of patients.

关 键 词：抑郁症 人工智能 深度学习 情感类别 个性化护理 

分 类 号：R473.74[医药卫生—护理学] R395[医药卫生—临床医学]