Minimal dataset for the study.
包含神经疾病合成病史文本的数据集，用于评估ChatGPT在神经学诊断中的准确性。
基本信息
资源简介
Minimal dataset for the study.
【数据集背景】
源站首次发布：2024-10-09。
【数据内容】
源站原始描述：ChatGPT, a general artificial intelligence, has been recognized as a powerful tool in scientific writing and programming but its use as a medical tool is largely overlooked. The general accessibility, rapid response time and comprehensive training database might enable ChatGPT to serve as a diagnostic augmentation tool in certain clinical settings. The diagnostic process in neurology is often challenging and complex. In certain time-sensitive scenarios, rapid evaluation and diagnostic decisions…
【数据结构与技术规格】
文件数 1 个，合计 399.25 KB。pone.0310028.s002.xlsx：application/vnd.openxmlformats-officedocument.spreadsheetml.sheet，399.25 KB。数据集 DOI：10.1371/journal.pone.0310028.s002。
【主题与分类】
源站学科分类：Cell Biology、Genetics、Molecular Biology、Neuroscience、Biotechnology、Immunology。主题标签：represent descriptive anamneses、atypical disease manifestations、02 %), furthermore、general artificial intelligence、various neurological settings、certain clinical settings、xlink "> chatgpt、evaluated whether chatgpt、general medical doctors、general medical doctor。
【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://plos.figshare.com/articles/dataset/Minimal_dataset_for_the_study_/27196505
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Nógrádi, Bernát; Polgár, Tamás Ferenc; Meszlényi, Valéria; Kádár, Zalán; Hertelendy, Péter; Csáti, Anett; et al. (2024). Minimal dataset for the study.. PLOS ONE. Dataset
下载信息
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使用方式
数据集获取（Figshare）
- 源站标题：Minimal dataset for the study.
- DOI：10.1371/journal.pone.0310028.s002
- 发布日期：2024-10-09
- 文件数：1 个
- 文件总体积：399.25 KB
- 源站页面：https://plos.figshare.com/articles/dataset/Minimal_dataset_for_the_study_/27196505
命令行下载
curl -L -o "pone.0310028.s002.xlsx" "https://ndownloader.figshare.com/files/49702502"
文件清单
pone.0310028.s002.xlsx（399.25 KB）
文件总体积 399.25 KB（源站 API 实测）。
数据说明
ChatGPT, a general artificial intelligence, has been recognized as a powerful tool in scientific writing and programming but its use as a medical tool is largely overlooked. The general accessibility, rapid response time and comprehensive training database might enable ChatGPT to serve as a diagnostic augmentation tool in certain clinical settings. The diagnostic process in neurology is often challenging and complex. In certain time-sensitive scenarios, rapid evaluation and diagnostic decisions are needed, while in other cases clinicians are faced with rare disorders and atypical disease manifestations. Due to these factors, the diagnostic accuracy in neurology is often suboptimal. Here we evaluated whether ChatGPT can be utilized as a valuable and innovative diagnostic augmentation tool in various neurological settings. We used synthetic data generated by neurological experts to represent descriptive anamneses of patients with known neurology-related diseases, then the probability for an appropriate diagnosis made by ChatGPT was measured. To give clarity to the accuracy of the AI-determined diagnosis, all cases have been cross-validated by other experts and general medical doctors as well. We found that ChatGPT-determined diagnostic accuracy (ranging from 68.5% ± 3.28% to 83.83% ± 2.73%) can reach the accuracy of other experts (81.66% ± 2.02%), furthermore, it surpasses the probability of an appropriate diagnosis if the examiner is a general medical doctor (57.15% ± 2.64%). Our results showcase the efficacy of general artificial intelligence like ChatGPT as a diagnostic augmentation tool in medicine. In the future, AI-based supporting tools might be useful amendments in medical practice and help to improve the diagnostic process in neurology.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0310028.s002（source: https://plos.figshare.com/articles/dataset/Minimal_dataset_for_the_study_/27196505）。
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