基于蚁群聚类算法的胎儿体重预测  

Estimating Fetal Weight Based on Ant Colony Clustering Algorithm

作　　者：薛景[1] 秦长海[2] 

机构地区：[1]扬州职业大学信息工程学院,江苏扬州225009 [2]中国船舶重工集团723研究所

出　　处：《计算机时代》2010年第11期4-6,10,共4页Computer Era

摘　　要：产前准确估计胎儿体重在产科临床中具有非常重要的意义。文章提出了基于蚁群聚类算法估测胎儿体重的方法,试图探索孕妇身高、体重、双顶径、股骨长度等与胎儿体重的关系。以孕妇身高、体重、宫高、腹围、双顶径、股骨长、羊水池的深度等综合数据建立模型,通过对100例临床资料的预测,正确率为89%,对巨大儿以及低体重儿的正确率为88%。此预测结果表明,蚁群聚类算法预测胎儿体重的方法具有一定的可行性。The accurate prenatal estimation of fetal weight is of important significance in obstetrical practice. This paper presents a method based on ant colony clustering algorithm for estimating fetal weight, which attempts to explore the relation of fetal weight and the data about pregnant woman such as height, weight, biparietal diameter and femur length. The model is constructed by using the integrated data of pregnant woman, including height, weight, fundal height, abdominal circumference, biparietal diameter, femur length and amniotic fluid pool depth. The 100 cases in clinical data were predicted with 89% accuracy, macrosomia and low birth weight infants with 88% accuracy. The prediction results show that the method based on ant colony clustering algorithm for estimating fetal weight has certain feasibility.

关 键 词：蚁群算法 人工智能 聚类 胎儿体重 

分 类 号：TP317[自动化与计算机技术—计算机软件与理论]