CAJ | 학술논문

目的：探讨人工神经网络模型在对急性应激障碍预警中的应用。方法通过现场流行病学整群抽样调查获取研究对象及有关信息；急性应激障碍确诊根据中国精神疾病分类( CCMD-3)诊断标准，并参照国际疾病分类第10版( ICD-10)相关内容。采用个性指标，认知评价，应对方式，社会支持，情绪指标，植物神经功能评定等指标；数据库建立采用 SPSS17.0软件，建立神经网络模型( ANN)。结果积累从2008年1月~2012年12月军队及地方突发事件应对人员,及医院门急诊采集病例近1000人，确诊急性应急障碍患者97人，患病率为9%。从被研究者中抽取急性应激障碍患者和非急性应激障碍者各97名为建模对象，将其情绪因子、性格指标、认知指标、植物神经指标等7个变量作为网络的输入层，进行 ANN的拟合。所建模型的预测精度为96%；能够正确预测建模对象中95.3%的非急性应激障碍患者，95.1%的急性应激障碍患者；输入变量敏感性系数排在前四位的依次为焦虑素质、认知功能、应对能力和植物神经功能。结论 ANN 在急性应激障碍(预测)中精度较高，具有一定的开发应用前景。
목적：탐토인공신경망락모형재대급성응격장애예경중적응용。방법통과현장류행병학정군추양조사획취연구대상급유관신식；급성응격장애학진근거중국정신질병분류( CCMD-3)진단표준，병삼조국제질병분류제10판( ICD-10)상관내용。채용개성지표，인지평개，응대방식，사회지지，정서지표，식물신경공능평정등지표；수거고건립채용 SPSS17.0연건，건립신경망락모형( ANN)。결과적루종2008년1월~2012년12월군대급지방돌발사건응대인원,급의원문급진채집병례근1000인，학진급성응급장애환자97인，환병솔위9%。종피연구자중추취급성응격장애환자화비급성응격장애자각97명위건모대상，장기정서인자、성격지표、인지지표、식물신경지표등7개변량작위망락적수입층，진행 ANN적의합。소건모형적예측정도위96%；능구정학예측건모대상중95.3%적비급성응격장애환자，95.1%적급성응격장애환자；수입변량민감성계수배재전사위적의차위초필소질、인지공능、응대능력화식물신경공능。결론 ANN 재급성응격장애(예측)중정도교고，구유일정적개발응용전경。
Objective To explore an artificial neural network model in the application of early warning system for Acute Stress Disorder (ASD) screening in the community. Methods The subjects and related information were obtained by Field Epidemiology cluster sample; ASD was diagnosed by Chinese Classification of Mental Disorders (CCMD-3) diagnostic criteria and International Classification of Diseases 10th edition (ICD-10); Using indicators of personality, cognitive appraisal, coping styles, social support, sentiment index, evaluating indicators such as plant nerve function; SPSS13.0 software was adopted to establish the database, and the Artificial Neural Network (ANN) was established. Results Accumulation from 2008 to 2012, the army and local emergency responders, and hospital screened the nearly 1000 people, 97 of them were diagnosed acute stress disorder (9%). such as emotion factor, character index, cognitive index, index of plant nerve, 7 variables as input layer of network, fitting for ANN. The model prediction accuracy is 95%; correctly forecasting modeling objects in 95.3% of patients with acute stress disorder, and 95.1% of the patients with non acute stress disorder. According to the sensitivity coefficient, the top four were anxiety character, cognitive function, response ability and plant nerve function. Conclusion ANN carries a high accuracy in ASD screening (prediction) in community which has wide application prospect.