The HyKGE framework can be extended to other domains beyond the medical field by adapting the knowledge graph and the prompts used in the framework to suit the specific domain requirements. Here are some ways to extend HyKGE to other domains:
Domain-specific Knowledge Graph: Create a domain-specific knowledge graph that captures the entities, relations, and attributes relevant to the new domain. This knowledge graph will serve as the source of external information for the retrieval-augmented generation process.
Customized Prompts: Develop prompts tailored to the new domain's context and requirements. These prompts should guide the LLMs in generating hypothesis outputs that align with the specific domain knowledge.
Fine-tuning LLMs: Fine-tune the LLMs on data from the new domain to enhance their understanding and performance in generating accurate responses. This step is crucial for ensuring that the LLMs can effectively leverage the domain-specific knowledge graph.
Evaluation and Validation: Conduct thorough evaluation and validation of the framework in the new domain to ensure its effectiveness and reliability. This may involve testing on domain-specific datasets and gathering feedback from domain experts.
By customizing the knowledge graph, prompts, and fine-tuning process to suit the characteristics of the new domain, the HyKGE framework can be successfully extended beyond the medical field to other domains such as finance, legal, or technology.