基于逻辑回归的近邻分类耦合算法在医学骨科分类应用
Application in Medical Orthopedic Classification of Coupling Nearest Neighbor Classification Algorithm Based on Logistic Regression
王宣谕1
作者信息
- 1. 西南交通大学,四川 成都 611756
- 折叠
摘要
随着现代医学的迅速发展,生物力学可以用来模拟人体机械组成各部分之间的关系,根据骨科患者的生物力学特征可以预测患者的症状类别,为临床诊断提供依据.文章为进一步提高预测分类的准确性,结合机器学习理论以最近邻算法分类及逻辑回归耦合算法来进行医学方面的骨科分类,通过双算法准确度判断的耦合结果进行进一步判断,丰富算法的计算维度,进一步提高了分类准确率的精度.
Abstract
With the rapid development of modern medicine,biomechanics can be used to simulate the relationship between the mechanical components of the human body,and the category of symptoms of patients can be predicted according to the biomechanical characteristics of orthopedic patients,providing a basis for clinical diagnosis.In order to further improve the accuracy of prediction classification,this paper combines Machine Learning theory to classify orthopedics in medicine with Nearest Neighbor algorithm classification and Logistic Regression coupling algorithm,and further judges through the coupling results of dual algorithm accuracy judgment,enriches the calculation dimension of the algorithm,and further improves classification accuracy.
关键词
最近邻分类器/耦合算法/生物特征Key words
Nearest Neighbor classifier/coupling algorithm/biological characteristics引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据