Our submission demonstrates improved TNM staging accuracy in lung cancers using ChatGPT in Japanese radiology reports, suggesting promise for AI applications.
We describe our submission to the RR-TNM subtask of the NTCIR-17 MedNLP-SC shared task. In the RR-TNM subtask, we developed our system for automatic extraction and classification of the TNM staging from Japanese radiology reports of lung cancers. In our system, zero-shot classification and prompt engineering were performed using ChatGPT and LangChain, respectively. According to the accuracies calculated by the organizers of the RR-TNM subtask, the accuracies of N and M factors in the TNM staging were higher in our submission than in the other submissions. These results indicate that our system with ChatGPT and LangChain may be promising.
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Nishio et al. (2023) studied this question.
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