تقرير
RJUA-QA: A Comprehensive QA Dataset for Urology
| العنوان: | RJUA-QA: A Comprehensive QA Dataset for Urology |
|---|---|
| المؤلفون: | Lyu, Shiwei, Chi, Chenfei, Cai, Hongbo, Shi, Lei, Yang, Xiaoyan, Liu, Lei, Chen, Xiang, Zhao, Deng, Zhang, Zhiqiang, Lyu, Xianguo, Zhang, Ming, Li, Fangzhou, Ma, Xiaowei, Shen, Yue, Gu, Jinjie, Xue, Wei, Huang, Yiran |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language |
| الوصف: | We introduce RJUA-QA, a novel medical dataset for question answering (QA) and reasoning with clinical evidence, contributing to bridge the gap between general large language models (LLMs) and medical-specific LLM applications. RJUA-QA is derived from realistic clinical scenarios and aims to facilitate LLMs in generating reliable diagnostic and advice. The dataset contains 2,132 curated Question-Context-Answer pairs, corresponding about 25,000 diagnostic records and clinical cases. The dataset covers 67 common urological disease categories, where the disease coverage exceeds 97.6\% of the population seeking medical services in urology. Each data instance in RJUA-QA comprises: (1) a question mirroring real patient to inquiry about clinical symptoms and medical conditions, (2) a context including comprehensive expert knowledge, serving as a reference for medical examination and diagnosis, (3) a doctor response offering the diagnostic conclusion and suggested examination guidance, (4) a diagnosed clinical disease as the recommended diagnostic outcome, and (5) clinical advice providing recommendations for medical examination. RJUA-QA is the first medical QA dataset for clinical reasoning over the patient inquiries, where expert-level knowledge and experience are required for yielding diagnostic conclusions and medical examination advice. A comprehensive evaluation is conducted to evaluate the performance of both medical-specific and general LLMs on the RJUA-QA dataset. Our data is are publicly available at \url{https://github.com/alipay/RJU_Ant_QA}. Comment: An initial version |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2312.09785 |
| رقم الأكسشن: | edsarx.2312.09785 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |