Benchmarking Large Language Models for Cervical Spondylosis Article Swipe
Boyan Zhang
,
Yueqi Du
,
Wanru Duan
,
Zan Chen
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.2196/55577
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.2196/55577
Cervical spondylosis is the most common degenerative spinal disorder in modern societies. Patients require a great deal of medical knowledge, and large language models (LLMs) offer 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 in clinical work and internet consultations. The accuracy of the answers provided by LLMs was evaluated and graded by 3 experienced spinal surgeons. Comparative analysis of responses showed that all LLMs could provide satisfactory results, and that among them, GPT-4 had the highest accuracy rate. Variation across each section in all LLMs revealed their ability boundaries and the development direction of artificial intelligence.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.2196/55577
- OA Status
- gold
- Cited By
- 3
- References
- 11
- Related Works
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4400694678Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.2196/55577Digital Object Identifier
- Title
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Benchmarking Large Language Models for Cervical SpondylosisWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-07-16Full publication date if available
- Authors
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Boyan Zhang, Yueqi Du, Wanru Duan, Zan ChenList of authors in order
- Landing page
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https://doi.org/10.2196/55577Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.2196/55577Direct OA link when available
- Concepts
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Preprint, Benchmarking, Cervical spondylosis, Computer science, Medicine, World Wide Web, Management, Economics, Alternative medicine, PathologyTop concepts (fields/topics) attached by OpenAlex
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3Total citation count in OpenAlex
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2025: 3Per-year citation counts (last 5 years)
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11Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| corresponding_author_ids | https://openalex.org/A5015090426 |
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| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I183519381 |
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