Research on Intelligent Analysis and Recognition System of Medical Data Based on Deep Learning

With the explosive growth in the amount of medical data, traditional data analysis methods can hardly meet the demand, especially in complex medical tasks such as disease diagnosis, patient monitoring and personalized treatment. A deep learning-based system for intelligent analysis and recognition of medical data has emerged, which is capable of automatically extracting features from massive data and efficiently learning through multi-layer neural networks, thus significantly improving diagnostic accuracy and medical efficiency. The system not only covers a variety of deep learning models, such as recurrent neural networks, long and short-term memory networks, gated recurrent units, attention mechanisms, and graph convolutional neural networks, but also combines pre-training models and autoencoders to achieve more accurate data analysis and recognition. Through the combined application of these technologies, it can help doctors make quick and accurate decisions to improve the treatment outcome and quality of life of patients.