人工智能自动化健康经济建模:一个案例研究来评估大型语言模型的潜在应用
Tim Reason1, William Rawlinson2, Julia Langham2
1Estima Scientific, Mediaworks, 191 Wood Ln, London, W12 7FP, UK. tim.reason@estima-sci.com.
PharmacoEconomics - open
|February 10, 2024
概括
生成式预训练变压器4 (GPT-4) 可以自动化健康经济模型编程,准确地复制非小细胞肺癌和细胞癌的复杂分析. 这表明了更快,更便宜的模型开发的潜力.
科学领域:
- 卫生经济学 卫生经济学
- 人工智能的人工智能是人工智能.
- 计算建模计算建模
背景情况:
- 像生成预训练变压器4 (GPT-4) 这样的大型语言模型 (LLM) 证明了人类级代码生成能力.
- 本研究调查了使用GPT-4用于自动化健康经济模型编程的可行性.
研究的目的:
- 评估GPT-4能够自动编程两个已发表的健康经济分析的能力.
- 将人工智能生成的模型与人类编程的模型进行准确性和效率的比较.
主要方法:
- 为非小细胞肺癌 (NSCLC) 和细胞癌 (RCC) 选择了两个分区生存模型.
- 详细提示描述模型方法,假设和参数,提供给GPT-4.
- 生成的R脚本被复制了15次,并与已发表的结果进行了比较.
主要成果:
- 在复制NSCLC模型时,GPT-4实现了高精度 (93%无错误).
- RCC模型复制需要稍微简化,60%的人工智能生成的模型在调整后没有错误.
- 无错误的模型复制了公布的增量成本效益比率在1%以内.
结论:
- GPT-4显示出对自动化健康经济模型构建的承诺,可能减少开发时间和成本.
- 需要进一步的研究来证实在各种健康经济模型中普遍性.
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