大规模语言模型在慢性眼病管理中的应用:范围综述表格
包含一篇关于大语言模型在慢性眼病管理中的范围综述的表格数据,总结了模型在筛查、诊断、治疗推荐中的应用及挑战。

基本信息
资源简介
大规模语言模型在慢性眼病管理中的应用:范围综述表格
【一句话概览】
本数据集是 figshare 公开的文本数据集,收录 1 个文件、合计 176.84 KB,主题涵盖 large language models、chronic ocular diseases、multimodal data、clinical decision support、full process management,可用于医学自然语言处理(实体识别、信息抽取等),CC BY 4.0 许可开放获取。
【数据集背景】
本数据集源站标题为《Table 1_Large language models in the management of chronic ocular diseases: a scoping review.docx》。配套论文《Large language models as assistance for glaucoma surgical cases: a ChatGPT vs. Google Gemini comparison》发表于 Graefe''s Archive for Clinical and Experimental Ophthalmology(2024),DOI:10.1007/s00417-024-06470-5。源站首次发布:2025-06-18。
【数据内容】
源站原始描述:Large language models, a cutting-edge technology in artificial intelligence, are reshaping the new paradigm of chronic ocular diseases management. In this study, we comprehensively examined the current status and trends in the application of large language models in major blinding chronic ocular diseases such as glaucoma, cataract, and diabetic retinopathy through a systematic scoping review approach. We conducted this review based on the Preferred Reporting Items for Systematic Reviews and Meta…
【数据结构与技术规格】
文件数 1 个,合计 176.84 KB。Table 1_Large language models in the management of chronic ocular diseases: a scoping review.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,176.84 KB。数据集 DOI:10.3389/fcell.2025.1608988.s001。
【主题与分类】
源站学科分类:Cell Biology。主题标签:large language models、chronic ocular diseases、multimodal data、clinical decision support、full process management。
【适用方向】
文本类数据可用于医学自然语言处理,如命名实体识别、信息抽取与文本分类。
【获取与许可】
源站页面:https://frontiersin.figshare.com/articles/dataset/Table_1_Large_language_models_in_the_management_of_chronic_ocular_diseases_a_scoping_review_docx/29346806
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Zhang, Jiatong; Song, Xiaoxi; Tian, Bocheng; Tian, Mingke; Zhang, Zhichang; Wang, Jing; et al. (2025). Table 1_Large language models in the management of chronic ocular diseases: a scoping review.docx. Frontiers. Dataset
下载信息
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使用方式
数据集获取(Figshare)
- 源站标题:Table 1_Large language models in the management of chronic ocular diseases: a scoping review.docx
- DOI:10.3389/fcell.2025.1608988.s001
- 发布日期:2025-06-18
- 文件数:1 个
- 文件总体积:176.84 KB
- 源站页面:https://frontiersin.figshare.com/articles/dataset/Table_1_Large_language_models_in_the_management_of_chronic_ocular_diseases_a_scoping_review_docx/29346806
命令行下载
curl -L -o "Table 1_Large language models in the management of chronic ocular diseases: a scoping review.docx" "https://ndownloader.figshare.com/files/55456235"
文件清单
Table 1_Large language models in the management of chronic ocular diseases: a scoping review.docx(176.84 KB)
文件总体积 176.84 KB(源站 API 实测)。
数据说明
Large language models, a cutting-edge technology in artificial intelligence, are reshaping the new paradigm of chronic ocular diseases management. In this study, we comprehensively examined the current status and trends in the application of large language models in major blinding chronic ocular diseases such as glaucoma, cataract, and diabetic retinopathy through a systematic scoping review approach. We conducted this review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extended to characterize the application of large language models in the field of chronic ocular diseases. The study reveals that large language models demonstrate comparable efficacy to experts in disease screening, diagnostic decision-making, personalized precision treatment recommendation, and accessibility of healthcare resources by integrating multimodal clinical data. However, the application of the technology still faces a triple challenge: (1) the limitation of model generalization ability due to the multimodal nature of clinical data; (2) the ethical controversy caused by the insufficient interpretability of algorithms; and (3) the lack of a standardized validation framework. Future directions emphasize the need for specialized model training, multimodal algorithm optimization, the establishment of a multinational multicenter clinical validation platform, and the construction of an ethical framework for dynamic regulation. Large language models are expected to evolve from an assisted decision-making tool to a core component of precision medicine for chronic ocular diseases, and ultimately to achieve an ecosystem of energy-efficient full-cycle management of chronic ocular diseases.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.3389/fcell.2025.1608988.s001(source: https://frontiersin.figshare.com/articles/dataset/Table_1_Large_language_models_in_the_management_of_chronic_ocular_diseases_a_scoping_review_docx/29346806)。
需要用于商业化训练或医疗器械注册(NMPA/FDA)?
公开数据往往缺乏完整的病理回证与专家标注。千方医数集依托陕川双基地与超十家三甲医院直连,提供完全合规、去标识化、支持注册级质控的专病数据集交易服务。




