تقرير
K-QA: A Real-World Medical Q&A Benchmark
| العنوان: | K-QA: A Real-World Medical Q&A Benchmark |
|---|---|
| المؤلفون: | Manes, Itay, Ronn, Naama, Cohen, David, Ber, Ran Ilan, Horowitz-Kugler, Zehavi, Stanovsky, Gabriel |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language, Computer Science - Human-Computer Interaction, Computer Science - Machine Learning |
| الوصف: | Ensuring the accuracy of responses provided by large language models (LLMs) is crucial, particularly in clinical settings where incorrect information may directly impact patient health. To address this challenge, we construct K-QA, a dataset containing 1,212 patient questions originating from real-world conversations held on K Health (an AI-driven clinical platform). We employ a panel of in-house physicians to answer and manually decompose a subset of K-QA into self-contained statements. Additionally, we formulate two NLI-based evaluation metrics approximating recall and precision: (1) comprehensiveness, measuring the percentage of essential clinical information in the generated answer and (2) hallucination rate, measuring the number of statements from the physician-curated response contradicted by the LLM answer. Finally, we use K-QA along with these metrics to evaluate several state-of-the-art models, as well as the effect of in-context learning and medically-oriented augmented retrieval schemes developed by the authors. Our findings indicate that in-context learning improves the comprehensiveness of the models, and augmented retrieval is effective in reducing hallucinations. We make K-QA available to to the community to spur research into medically accurate NLP applications. Comment: The data and the evaluation script are available at https://github.com/Itaymanes/K-QATest. Results and model comparisons can be viewed at https://huggingface.co/spaces/Itaykhealth/K-QATest |
| نوع الوثيقة: | Working Paper |
| الوصول الحر: | http://arxiv.org/abs/2401.14493Test |
| رقم الانضمام: | edsarx.2401.14493 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |