Frontiers in Medical Science Research, 2024, 6(11); doi: 10.25236/FMSR.2024.061105.
Jinzhu Yang
AI Research, Dyania Health Inc, Jersey City, New Jersey, 07310, United States
Online consultation has become an important way for people to seek advice from doctors during the epidemic, but the lack of face-to-face communication and differences in patients' self-reported symptoms make it difficult for doctors to accurately assess the condition. In this paper, a Chinese medical text matching model combining twin network and knowledge distillation technology is proposed, and a medical question answering system is established. The system uses the Siamese-UniLM model to capture deep text information, greatly improving the accuracy and F1 value, and reducing model parameters and computing resources through knowledge distillation technology to achieve efficient online reasoning. The experimental results show that the model significantly improves the system response speed and resource utilization efficiency, and provides a reliable solution for providing scientific and accurate medical advice.
Medical Text Comparison, Twin Networks, Knowledge Distillation, Online Consultation
Jinzhu Yang. Research on the Application of Medical Text Matching Technology Combined with Twin Network and Knowledge Distillation in Online Consultation. Frontiers in Medical Science Research (2024), Vol. 6, Issue 11: 25-29. https://doi.org/10.25236/FMSR.2024.061105.
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