Summary of Medkp: Medical Dialogue with Knowledge Enhancement and Clinical Pathway Encoding, by Jiageng Wu et al.
MedKP: Medical Dialogue with Knowledge Enhancement and Clinical Pathway Encoding
by Jiageng Wu, Xian Wu, Yefeng Zheng, Jie Yang
First submitted to arxiv on: 11 Mar 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed Medical dialogue with Knowledge enhancement and clinical Pathway encoding (MedKP) framework integrates an external knowledge enhancement module through a medical knowledge graph and an internal clinical pathway encoding via medical entities and physician actions. This framework is designed to improve the accuracy of large language models (LLMs) in generating medical responses, which has been less explored due to LLMs’ insufficient medical knowledge. By evaluating MedKP on two real-world online medical consultation datasets, the authors demonstrate that it surpasses multiple baselines and mitigates the incidence of hallucinations, achieving a new state-of-the-art performance. The framework’s effectiveness is further revealed through extensive ablation studies. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper presents a way to improve large language models (LLMs) so they can help with medical consultations. Right now, LLMs are good at answering simple questions, but when it comes to having a conversation about a patient’s symptoms and treatment options, they often make mistakes or make things up. The new framework, called MedKP, helps LLMs understand more about medicine by giving them information from a big database of medical knowledge. This makes the conversations they have with patients more accurate and reliable. The paper shows that MedKP works better than other methods on two large datasets of online medical consultations. |
Keywords
» Artificial intelligence » Knowledge graph
