Abstract: When filling electronic medical record data, a fixed filling value will result in low completeness of the filled data, affecting the quality of the filling method. Therefore a dynamic filling algorithm for missing values in multimodal data of electronic medical records is proposed. The obtained multimodal data of electronic medical records is fused, an electronic medical record data model is constructed, corresponding sequence features are mined, and the missing value positions of electronic medical record data is detected under the action of forward propagation network. The missing values of electronic medical record data is estimated based on the established time series matrix. Using the estimated missing values as initial values, the electronic medical record data is preliminarily filled in, and then the fuzzy clustering algorithm is applied to perform preliminary clustering. By continuously updating the clustering centers and filling values, the optimal filling value is calculated to achieve the filling of missing values in the electronic medical record data. The experimental results show that the designed filling algorithm can accurately fill in electronic medical record data, and the completeness of the filled electronic medical record data is 0. 95, indicating high data quality.

Key words: electronic medical records, multimodal data, data missing values, fill in missing values, filling algorithm, missing value detection