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聊天GPT和职业治疗:对生成程序可行性的研究

Tadatoshi Inoue¹, Shogo Sawamura¹, Tatsuya Sera¹

¹Department of Rehabilitation, Heisei College of Health Sciences, Gifu, JPN.

|June 10, 2025

概括

生成式预训练变压器 (GPT) 证明了为中风患者创建个性化职业治疗 (OT) 计划的能力有限,突出了在OT程序开发中需要专业知识的需求.

科学领域:

医疗信息学医疗信息学
康复医学康复医学康复医学
医疗保健中的人工智能

背景情况:

大型语言模型 (LLM) 在医学中越来越多地应用.
在创建职业治疗 (OT) 计划方面,LLM的潜力在很大程度上尚未被探索.
生成式预训练型变压器 (GPT) 是一个著名的LLM,在医疗保健领域具有潜在的应用.

研究的目的:

评估GPT在产生职业治疗 (OT) 计划方面的能力.
评估GPT生成的OT程序的质量和特异性,与由人类专家开发的OT程序相比.

主要方法:

根据五个关于中风患者有心理症状的病例报告,GPT被促使创建OT程序.
五位职业治疗师 (OTR) 评估了GPT生成的程序.
量化了GPT生成的程序和OTR创建的程序之间的一致程度.

主要成果:

在所有情况下,GPT生成的OT程序与OTR创建的程序的一致性很低 (得分≤2/4).
生成的内容被描述为一般性,缺乏具体性,个性化和专业化.
GPT努力将患者特定的生活背景和专业知识纳入其中.

结论:

目前,GPT在创建全面和个性化的OT计划方面存在重大局限性.
在特定的,有限的OT程序创建方面,GPT可能具有潜在的实用性.
需要进一步的研究来解决GPT在OT等专业医疗应用中的局限性.

关键词:

聊天gpt-4 评价创建一个计划的计划.大型语言模型.职业疗法计划职业疗法计划程序生成程序生成程序生成程序

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