Research on Demand Prediction for Coronary Stents Based on Deep Learning

Objective This study aims to predict the demand for coronary stents based on different deep learning models, in order to optimize the supply plan of coronary stents and improve the efficiency of supply and use.

Methods The centralized procurement data of coronary stents in a large tertiary hospital from January 2022 to August 2024 are selected, three deep learning models are used to predict the demand, the learning effect of the model is evaluated based on the MSE curve, and the prediction results of the dataset through different evaluation indicators are verified and the prediction error is evaluated.

Results The MSE curve indicates that the Transformer model exhibits the strongest feature extraction and pattern recognition capabilities in this task, and the predicted demand evaluation index system verifies that the prediction results based on the Transformer model are close to the actual values.

Conclusion This study has established a deep learning based coronary stent supply model, which effectively predicts the demand for coronary stents and provides reference for optimizing hospital stocking plans, thereby ensuring the use and supply of coronary stents.