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Discussion on Using RNN Model to Optimize the Accuracy and Efficiency of Medical Image Recognition

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  • Zhang, Minkang

Abstract

With the continuous development of artificial intelligence technology, especially represented by deep learning, recurrent neural networks have made revolutionary breakthroughs in medical image recognition. This paper first introduces the concept of RNN pattern and its application in medical image recognition. By analyzing various applications of RNN in medical image classification, we explore how to improve the accuracy and computational efficiency of medical image recognition by optimizing the RNN model. Specifically, the gating mechanism, convolutional neural network (CNN) construction, lightweight technology and other optimization strategies, multi-modal learning and attention mechanism input are discussed. Finally, the prospects and challenges of the RNN model in medical image recognition are summarized, and the future research directions in this field are also discussed.

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  • Zhang, Minkang, 2025. "Discussion on Using RNN Model to Optimize the Accuracy and Efficiency of Medical Image Recognition," European Journal of AI, Computing & Informatics, Pinnacle Academic Press, vol. 1(2), pages 66-72.
    • Handle: RePEc:dba:ejacia:v:1:y:2025:i:2:p:66-72
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