基于音频分析技术的甲状腺疾病诊断方法
Diagnostic method for thyroid disease using audio analysis technology
刘彤 1张博维 1冯超 1顾毅 1高青山1
作者信息
- 1. 四川省人民医院甲状腺外科,四川成都 610072
- 折叠
摘要
通过结合基于SMOTE数据扩充方法对复杂音频数据的处理能力以及GA-SVM的准确预测能力,提出一种基于SMOTE数据扩充算法的GA-SVM模型,并将其应用于甲状腺疾病的诊断中.实验结果表明,本文方法在甲状腺疾病分类诊断方面表现出良好的性能.相较于其他方法,本文方法在诊断效果方面表现更佳,在甲状腺疾病的分类诊断中具有更高的适用性.
Abstract
By combining the ability of SMOTE data augmentation method to process complex audio data with the accurate prediction ability of GA-SVM,a GA-SVM model based on SMOTE data augmentation algorithm is proposed and applied to the diagnosis of thyroid diseases.The results demonstrate the excellent performance of the proposed method in the classification and diagnosis of thyroid diseases.Compared with other methods,the proposed method has better diagnostic efficacy and higher applicability in the classification and diagnosis of thyroid diseases.
关键词
甲状腺疾病/音频分析/GA-SVM模型/诊断方法Key words
thyroid disease/audio analysis/GA-SVM model/diagnostic method引用本文复制引用
基金项目
四川省国际科技创新项目(21GJHZ0066)
出版年
2024
NETL
NSTL
万方数据