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28 August 2023 Enhancing the effect of BERT model in the medical field based on the knowledge graph
Xuchang Han, Lin Zhang
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Proceedings Volume 12724, Second International Conference on Biomedical and Intelligent Systems (IC-BIS 2023); 127242J (2023) https://doi.org/10.1117/12.2687418
Event: Second International Conference on Biomedical and Intelligent Systems (IC-BIS2023), 2023, Xiamen, China
Abstract
Knowledge graph is a kind of knowledge representation, which captures information about entities, entity attributes and relationships between entities in a structured way, and is widely used in intelligent retrieval, recommendation systems, intelligent question answering, etc. Knowledge map is a graphical representation of the relationship between different concepts and topics in a specific field, while BERT is a most advanced language model that can understand the context and meaning of words in text. By combining the two methods of medical knowledge graph (MKG) and the bidirectional encoder representation of BERT model, it shows hope in improving medical information retrieval and decision-making, and can create a more comprehensive and accurate representation of medical knowledge, which can be used to guide clinical decision-making and improve the prognosis of patients, and ultimately improve the effect of BERT in the medical field.
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Xuchang Han and Lin Zhang "Enhancing the effect of BERT model in the medical field based on the knowledge graph", Proc. SPIE 12724, Second International Conference on Biomedical and Intelligent Systems (IC-BIS 2023), 127242J (28 August 2023); https://doi.org/10.1117/12.2687418
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KEYWORDS
Data modeling
Machine learning
Design and modelling
Diseases and disorders
Semantics
Matrices
Transformers
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