Evaluation of Multimedia Courseware-Assisted Teaching Effect of Medical Images Based on the Deep Learning Algorithm.

Abstract

In order to improve the dynamic evaluation ability of medical image multimedia courseware-assisted teaching effect, the evaluation of medical image multimedia courseware-assisted teaching effect based on a deep learning algorithm is proposed. The statistical data analysis model of medical image multimedia courseware-assisted teaching effect is established to estimate its utilization rate and scale parameters. Based on the prediction of spatial attribute parameters, the classification big data mining model of medical image multimedia courseware-assisted teaching is constructed by using the deep learning algorithm, mining association rules and frequent item sets that can dynamically reflect the quality of medical image multimedia courseware-assisted teaching, and extracting the statistical feature of the dataset of constraint indicators of medical image multimedia courseware-assisted teaching effect to improve the teaching quality of medical imaging course. The simulation results show that this method has a better precision delivery effect, higher dynamic matching degree of teaching evaluation parameters, more than 90% reliability, and better clustering of statistical eigenvalues.