Research on Intelligent Optimization of Electronic Information Systems in Centers for Disease Control and Prevention Based on Deep Learning
With the continuous development of society,facing the increasing amount of data and increasingly complex public health problems,traditional information systems are no longer able to meet the needs of fast and accurate information processing,thereby affecting the efficiency of public health processing.Therefore,this article analyzes and studies the optimization strategies for the intelligence of electronic information systems in disease control centers by integrating the most advanced deep learning models.The research results indicate that the proposed optimization scheme significantly improves the accuracy and timeliness of information processing compared to existing systems,providing a more reliable scientific basis for health risk assessment and resource allocation.
deep learningcenter for disease control and preventionelectronic information systemsintelligence
NETL
NSTL
万方数据
