Method for diagnosing keratoconus cases based on machine learning

The invention relates to a method for diagnosing keratoconus cases based on machine learning. According to the method, a support vector machines-recursive feature elimination (SVM-RFE) algorithm and agradient boosting regression tree (ABDT) algorithm are applied to accurate diagnosis of the keratoco...

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Hauptverfasser: WANG SHUHANG, XU JIAHUI, PEI LEQI, CUI TONG, WANG YAN, JI SHUFAN, ZHANG LIN
Format: Patent
Sprache:chi ; eng
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Zusammenfassung:The invention relates to a method for diagnosing keratoconus cases based on machine learning. According to the method, a support vector machines-recursive feature elimination (SVM-RFE) algorithm and agradient boosting regression tree (ABDT) algorithm are applied to accurate diagnosis of the keratoconus cases. Furthermore for aiming at specific application cases, effective overall plan designing,process designing and algorithm parameter setting are performed. Through test of a large number of clinic instances, the diagnosis accuracy of the method is effectively improved and basically satisfies the requirement for clinic applications. 本发明涉及种基于机器学习诊断圆锥角膜病例的方法,首次将机器学习中的支持向量机-递归特征筛减算法(SVM-REF)及梯度提升树(GBDT)算法应用于圆锥角膜病例的精准诊断,并针对具体应用实例,进行了有效的总体方案设计、流程设计及算法参数设置。通过大量临床实例测试,该方法的诊断准确度明显提升并已基本满足临床应用。