摘要为了提高卫勤模拟训练的效果，基于战伤严重度评分并综合运用深度神经网络（DNN）建模技术，建立一种新的战伤数据增强模型（WTSS-DNN），用于准确统计卫勤模拟训练系统中的伤员数据，并构建满足卫勤组织指挥要求、符合战时伤员救治特征的战场模拟伤员。WTSS-DNN相较于传统的人工数据生成方法，在保持后果预测准确性和伤情合理性的前提下，可以自动化、大规模地生成战伤伤员数据，对战伤数据分析研究、战时伤员伤情快速评估及分级后送具有重要意义。

abstractsIn order to improve the outcome of medical service simulation training，an augmented model of war trauma data（WTSS-DNN）is developed based on the war trauma severity score and comprehensive application of deep neural network modeling technology. The model is used to augment the data of casualty in the medical service simulation training system，so as to simulate the battlefield casualty with the characteristics of casualty treatment in real combat conditions and meet the requirements of the medical service organization and commanding. Compared with the traditional method that generates the data of casualty manually，WTSS-DNN can automatically and massively generate the data of casualty on the premise of maintaining the accuracy of consequence prediction and the rationality of casualty conditions，which is of great significance for the analysis and research of the war trauma data，rapidly assessing casualties’ condition，and evacuating according to triaging.