Research on Knowledge Representation and Reasoning Mechanism of Neural Networks in Medical Question-Answering Systems

Abstract

This article focuses on the application of neural networks in medical question-answering systems, with a particular emphasis on the knowledge representation and reasoning mechanisms. Firstly, the characteristics and demands of the medical question-answering system were analyzed, and the limitations of traditional methods in dealing with complex medical knowledge were pointed out. Then, the advantages of neural networks in knowledge representation were elaborated in detail, including how methods such as distributed representation and graph neural network representation effectively capture the semantic and structural information of medical knowledge. In the reasoning mechanism section, reasoning methods based on attention mechanisms, memory networks, etc. are discussed, as well as how to utilize neural networks to achieve multi-hop reasoning and logical reasoning. Finally, the development prospects of the knowledge representation and reasoning mechanism of neural networks in medical question-answering systems are prospected, aiming to provide theoretical support for building more efficient and accurate medical question-answering systems.