北京生物医学工程2025，Vol.44Issue(3)：266-272,7.DOI:10.3969/j.issn.1002-3208.2025.03.007
基于时间序列特征的顿挫期圆锥角膜诊断模型
The diagnosis model for forme fruste keratoconus based on time series features
摘要
Abstract
Objective To explore the feasibility of constructing a diagnostic model for forme fruste keratoconus(FFKC)using time-series corneal curvature data obtained from the corneal visualization scheimpflug technology(Corvis ST)test.Methods This study included 88 cases(88 eyes)of FFKC patients,with an equal number of patients undergoing corneal refractive surgery selected as the control group.Utilizing the 140-frame corneal anterior/posterior surface profile data obtained from the Corvis ST test,a time-series corneal curvature dataset was constructed.Subsequently,classifiers for FFKC were constructed using both the random forest(RF)model and the long short-term memory-attention(LSTM-Attention)model.The models were validated using five-fold cross-validation.Results The RF model showed that using the 140-frame corneal curvature data as input features resulted in an AUC value of only 0.69.However,combining specific frame-derived curvature indices with dynamic corneal response(DCR)parameters from Corvis ST significantly improved the model's diagnostic efficiency,achieving a maximum AUC of 0.81.Compared to the RF methods,the LSTM-Attention model based on the time-series corneal curvature dataset further enhanced diagnostic efficiency,achieving an AUC of 0.87.When using the time-series curvature dataset of the anterior and posterior corneal surfaces as separate model inputs,the AUC values were 0.82 and 0.84,respectively.Conclusions Constructing an FFKC diagnostic model using a time-series corneal curvature dataset is feasible,and the LSTM-Attention model effectively enhances diagnostic efficiency.关键词
顿挫期圆锥角膜/曲率/时间序列/长短期记忆-注意力模型Key words
form fruste keratoconus/corneal curvature/time series/long short-term memory-attention model分类
医药卫生引用本文复制引用
孙铭,李林,张海霞..基于时间序列特征的顿挫期圆锥角膜诊断模型[J].北京生物医学工程,2025,44(3):266-272,7.基金项目
国家自然科学基金(32171304)资助 （32171304）
