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Benchmarking Large Language Models for Cervical Spondylosis
Boyan Zhang;
Yueqi Du;
Wanru Duan;
Zan Chen
ABSTRACT
Cervical spondylosis is the most common degenerative spinal disorder in modern societies. Patients require a lot of medical information, and large language models (LLMs) offers patients a novel and convenient tool for accessing medical advice. In this study, we collected the most frequently asked questions by patients with cervical spondylosis during diagnosis and internet consultation. By evaluating and grading the answers provided by three experienced spine surgeons, we analyzed the accuracy of LLMs in the field of cervical spondylosis. All LLMs can provide satisfactory results, while GPT-4 has the highest accuracy rate. Variation across different categories in all LLMs reveals the ability boundary and development direction of artificial intelligence.
Citation
Please cite as:
Zhang B, Du Y, Duan W, Chen Z
Benchmarking Large Language Models for Cervical Spondylosis