Construction of medical information knowledge graph question and answer system based on deep learning

Donghua Mo; Pingshan Liu

doi:10.1117/12.3036593

13 July 2024 Construction of medical information knowledge graph question and answer system based on deep learning

Donghua Mo, Pingshan Liu

Proceedings Volume 13208, Third International Conference on Biomedical and Intelligent Systems (IC-BIS 2024); 132081H (2024) https://doi.org/10.1117/12.3036593
Event: 3rd International Conference on Biomedical and Intelligent Systems (IC-BIS 2024), 2024, Nanchang, China

Abstract

In view of the shortcomings of existing medical information intelligent question-and-answer systems in terms of data sources, user needs understanding and answer accuracy, this research aims to build a medical information questionanswering system based on deep learning and knowledge graph. Through the utilization of the BERT-GCN model, as well as knowledge graph, intelligent question-and-answer, and network crawler technologies, we have gathered, extracted, and integrated medical data from the Internet extensively. The system's key features include a knowledge graph, keyword matching, and automatic question-and-answer capabilities, facilitating the retrieval and visualization of medical information knowledge. By efficiently answering questions, users are able to access the necessary medical knowledge and knowledge graph in a user-friendly manner. This system effectively assists patients and healthcare professionals in accessing, comprehending, and utilizing medical information, thereby advancing the progress of the healthcare industry

Citation Download Citation

Donghua Mo and Pingshan Liu "Construction of medical information knowledge graph question and answer system based on deep learning", Proc. SPIE 13208, Third International Conference on Biomedical and Intelligent Systems (IC-BIS 2024), 132081H (13 July 2024); https://doi.org/10.1117/12.3036593

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