CAJ | 학술논문

基于2006年1月至2010年12月北京市120急救中心的逐日脑血管急症接诊病例数据资料，首先探讨北京市急性脑血管疾病与气象要素的关系，选取不同季节的影响因子，然后根据概率积分方法将发病人数划分为4个级别，并采用人工神经元网络方法（artificial neural network，ANN）分别建立了北京市不同季节的急性脑血管疾病预测模型。研究结果表明：（1）急性脑血管疾病发病人数存在明显的季节性变化和日变化特征，冬春季发病人数高于夏、秋季，发病主要集中在早晨到中午的09-14时；（2）发病人数相对于气象要素存在明显的滞后效应，夏和冬秋季发病分别与高温高湿、冷空气活动有关；（3）脑血管疾病预测模型通过对新样本进行预报，除夏季外，完全准确率高于30％，预报误差≤±1级的准确率高于60％，研究成果对于预防急性脑血管疾病发病和调度120急救车辆等应急措施具有较好的科学参考价值。
기우2006년1월지2010년12월북경시120급구중심적축일뇌혈관급증접진병례수거자료，수선탐토북경시급성뇌혈관질병여기상요소적관계，선취불동계절적영향인자，연후근거개솔적분방법장발병인수화분위4개급별，병채용인공신경원망락방법（artificial neural network，ANN）분별건립료북경시불동계절적급성뇌혈관질병예측모형。연구결과표명：（1）급성뇌혈관질병발병인수존재명현적계절성변화화일변화특정，동춘계발병인수고우하、추계，발병주요집중재조신도중오적09-14시；（2）발병인수상대우기상요소존재명현적체후효응，하화동추계발병분별여고온고습、랭공기활동유관；（3）뇌혈관질병예측모형통과대신양본진행예보，제하계외，완전준학솔고우30％，예보오차≤±1급적준학솔고우60％，연구성과대우예방급성뇌혈관질병발병화조도120급구차량등응급조시구유교호적과학삼고개치。
Based on daily emergency case data of cerebrovascular disease in Beijing during 2006-2010, which are obtained from the Beijing urgent care centre (120).The association between the daily meteoro-logical factors and hospital emergency visits for cerebrovascular disease in different seasons in Beijing is ex-plored.Then we choose meteorological factors with regression method so as to obtain the forecast factors which are finally used to build forecast models in different seasons based on the ANN (artificial neural net-work)method,and the daily hospital visit numbers are divided into four grades by using multiple regres-sion probability grade analysis.The results show that:(1 )There are obvious seasonal and diurnal varia-tions in the number of acute cerebrovascular disease,the number of cases is significantly higher in spring and winter than in summer and autumn,and concentrate mainly in 09:00-14:00 BT.(2)The meteoro-logical factors have obvious hysteresis to induce the recurrence of cerebrovascular disease.In addition,sta-tistical results show that the condition of high temperature and humidity weather in summer or cold air ac-tivity in winter and autumn may aggravate disease.(3)The models in spring,autumn and winter are used to forecast daily disease grade of new samples,the test results show the complete accuracy exceeds 30%;If the difference between the forecasted grade and actual grade is no more than 1 ,the accuracy exceeds 60%.The research results offer scientific reference for preventing the development of cerebrovascular dis-ease and scheduling such emergency measures as 120 emergency vehicles.