Research on KG and LLM knowledge-enhanced pediatric diseases intelligent diagnosis

Wenhui Fu; Dongming Dai; Kunli Zhang; Xiaomei Liu; Hengxing Zhang; Lingxiang Ao; Jinlong Xiao

doi:10.1117/12.3032061

8 June 2024 Research on KG and LLM knowledge-enhanced pediatric diseases intelligent diagnosis

Wenhui Fu, Dongming Dai, Kunli Zhang, Xiaomei Liu, Hengxing Zhang, Lingxiang Ao, Jinlong Xiao

Proceedings Volume 13171, Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024); 131710U (2024) https://doi.org/10.1117/12.3032061
Event: 3rd International Conference on Algorithms, Microchips and Network Applications (AMNA 2024), 2024, Jinan, China

Abstract

Pediatric diseases are challenging to diagnose due to their complex and diverse characteristics. To assist doctors in diagnosis and help them make informed decisions, this paper proposes a Knowledge graph and Large language model Knowledge-Enhanced (KLKE) intelligent diagnosis model. The intelligent diagnosis task is treated as a text classification task, where the original Electronic Medical Record are input into MacBERT model encoder to obtain the contextual representation after key information enhancement and KG prompted LLM enhancement respectively. The final text representation is obtained by concatenating and merging the enhanced representations. Graph Convolutional Network is utilized to obtain the knowledge representation and the two representations are fused using a fusion method based on interactive attention mechanism. Experiments are conducted on PeEMR, and compared with models that only fuses triples and graph structures. The KLKE achieved an increase of 9.15% and 2.28% in F1_micro scores respectively.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Wenhui Fu, Dongming Dai, Kunli Zhang, Xiaomei Liu, Hengxing Zhang, Lingxiang Ao, and Jinlong Xiao "Research on KG and LLM knowledge-enhanced pediatric diseases intelligent diagnosis", Proc. SPIE 13171, Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024), 131710U (8 June 2024); https://doi.org/10.1117/12.3032061

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KEYWORDS

Diseases and disorders

Epilepsy

Education and training

Data modeling

Diagnostics

Performance modeling

Deep learning

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