基于呼吸波形特征参数时间序列的AECOPD预测方法

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中图分类号:TP391;R318 文献标志码:A 文章编号:1671-024X(2025)04-0007-06
AECOPD prediction method based on respiratory waveform feature parameterstimeseries
WANG Huiquan 1,2,3 , ZHAO Weibiao 1,2,3 , MENG Qingkai4, MA Jianxin4, TONG Zhaohui 5 , CAO Zhixin5 (1.SchoolofLifeSciences,Tiangong University,Tianjin3Oo387,China;2.Research CenterforFuture TextileTechnolo gy,Tiangong University,Tianjin 3Oo387, China; 3.Tianjin KeyLaboratoryof QualityControland Evaluation Techology forMedical Devics,Tiangong University,Tianjin 300387,China;4.BMC Medical Co.,Ltd.,Beijing 100041,China; 5.Beijing Chao-YangHospital,Capital Medical University,Beijing 1Ooo2O,China)
Abstract:To achieve early prediction of the events of acute exacerbation of chronic obstructive pulmonary disease (AECOPD),a patient respiratory waveform monitoring system based on remote ventilators was built. Daily parameters of ventilators usedby 29 patients who experienced disease exacerbation events and 29 patients in stable disease periods were collcted and recorded. Feature parameters reflecting the patient's respiratory rhythm were extracted from the respiratory waveforms. Multiple disease exacerbation prediction models were established using feature time series with diferent intervals from the patient's hospitalizationdate to evaluate the prediction models.The results showed that asthe prediction window increased,the predictive performanceof the model for disease exacerbation events first increased and then decreased.The efective prediction time window of the model was 3-4d,and after 3-4d ,the area value (AUC value) under the rececier operating characteristic (ROC) curve of the modelnolonger had statisticalsignificance; by feature time series,this modelcan make predictions in the early stages of disease progression,providing more intervention opportunities for disease prevention and treatment.
Key Words:chronic obstructive pulmonary disease(COPD); machine learning; time series ;telemedicine
慢性阻塞性肺疾病(chronic obstructive pulmonary disease,COPD)给患者的日常生活造成严重的困扰。(剩余11352字)