使用人工智能大语言模型作为康复医学中的临床工具:一个比较的试验案例
Liang Zhang1, Syoichi Tashiro2, Masahiko Mukaino3
1Department of Rehabilitation Medicine, Kyorin University School of Medicine, Japan.
Journal of rehabilitation medicine
|September 11, 2023
概括
人工智能语言模型在为中风患者生成康复处方和国际功能,残疾和健康分类 (ICF) 代码方面表现有前途. 这项技术可以帮助临床实践和康复医学教育.
科学领域:
- 康复医学 康复医学 康复医学
- 医疗保健中的人工智能
- 临床决策支持 临床决策支持
背景情况:
- 人工智能 (AI) 语言模型正在迅速发展.
- 它们在康复等专业医疗领域的应用正在出现.
- 有效制定康复计划和编码对于患者护理至关重要.
研究的目的:
- 评估人工智能语言模型在创建康复处方方面的有效性.
- 评估人工智能产生的国际功能,残疾和健康分类 (ICF) 代码的准确性.
- 为了将AI输出与中风病例的传统方法进行比较.
主要方法:
- 使用聊天生成预训练变压器-4 (ChatGPT-4) 来处理教科书中风病例.
- 使用AI模型生成医疗和康复处方和ICF代码.
- 将人工智能生成的内容与教科书答案和专家临床医生审查进行了比较.
主要成果:
- 聊天GPT-4成功地在几秒钟内为中风病例生成了全面的康复处方和ICF代码.
- 人工智能输出比教科书答案更广泛和更一般,提供了特定的治疗方法.
- 在ICF类别分配中发现了一个小错误,但ICF代码本身是准确的.
结论:
- 人工智能语言模型在制定康复处方和ICF代码方面具有潜在的实用性.
- 这些模型可以帮助临床实践,并增强康复医学的教育工具.
- 需要进一步的研究来探索AI在这个领域的全部能力和局限性.
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