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生成式人工智能GPT-4驱动的中药处方生成研究
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          陈祺焘 ,倪璟雯,徐 君,高晓涵,夏丽珍(三明市中西医结合医院药学部,福建 三明 365001)
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          中图分类号  R95      文献标志码  A      文章编号  1001-0408(2023)23-2825-04
          DOI  10.6039/j.issn.1001-0408.2023.23.02


          摘  要  目的  评估生成式人工智能(AIGC)中的GPT-4模型生成中药处方的安全性、适宜性,为AIGC赋能中医药行业提供研究
          思路。方法  将2020年版《中国药典》和第5版《中药学》作为语料,由GPT-4及基于GPT-4开发的实时联网模型(简称“联网模型”)
          对其进行深度学习。人工抽取近几年中医药类专家共识收录的临床案例,由GPT-4模型和联网模型根据诊断重新生成处方。由
          中医药学专家对GPT-4生成处方、联网模型生成处方以及专家共识处方进行盲评打分,同时通过图灵测试来评估GPT-4模型和联
          网模型是否具有与人类智能相当的能力。结果  GPT-4 模型生成的中药处方的平均分与人工处方比较,差异无统计学意义(P>
          0.05);联网模型生成处方的平均分与GPT-4模型生成的中药处方比较,差异无统计学意义(P>0.05)。模型生成处方在图灵测试
          中被误判为人工处方的占比达51.11%。结论  GPT-4模型生成的中药处方在安全性、适宜性方面已经具备一定的水平,且GPT-4
          模型通过了所设置的图灵测试;在诊疗过程中引入AIGC可能为临床中药的合理使用提供技术支撑。
          关键词  GPT-4;中药处方;生成式人工智能

          Generation of traditional Chinese medicine prescription driven by generative artificial intelligence GPT-4
          CHEN Qitao,NI Jingwen,XU Jun,GAO Xiaohan,XIA Lizhen(Dept.  of  Pharmacy,  Sanming  Integrated
          Medicine Hospital, Fujian Sanming 365001, China)

          ABSTRACT   OBJECTIVE  To  evaluate  the  safety  and  suitability  of  traditional  Chinese  medicine  prescriptions  generated  by
          generative  artificial  intelligence (AIGC),  and  to  provide  research  ideas  for  empowering  the  traditional  Chinese  medicine  industry
          with AIGC. METHODS Using the 2020 edition of Chinese Pharmacopoeia and the 5th edition of Traditional Chinese Medicine as
          corpus, GPT-4 and the real-time networking model developed based on GPT-4 (referred to as the “networking model”) were used
          for deep learning. The clinical cases included in the consensus of traditional Chinese medicine experts in recent years were extracted
          manually to regenerate prescriptions based on diagnosis using the GPT-4 model and networking model; traditional Chinese medicine
          experts  conducted  blind  evaluation  and  scoring  of  GPT-4  generated  prescriptions,  networking  model  generated  prescriptions,  and
          expert  consensus  prescriptions.  At  the  same  time,  Turing  testing  was  used  to  evaluate  whether  the  GPT-4  model  and  networking
          model  had  the  same  ability  as  human  intelligence.  RESULTS  The  average  score  of  traditional  Chinese  medicine  prescriptions
          generated by the GPT-4 model showed no statistically significant difference compared to manual prescriptions (P>0.05), while the
          average  score  of  prescriptions  generated  by  the  networking  model  showed  no  statistically  significant  difference  compared  to
          traditional  Chinese  medicine  prescriptions  generated  by  the  GPT-4  model  (P>0.05).  The  proportion  of  model-generated
          prescriptions  mistakenly  judged  as  manual  prescriptions  in  the  Turing  test  was  51.11%.  CONCLUSIONS  The  traditional  Chinese
          medicine  prescriptions  generated  by  the  GPT-4  model  have  reached  a  certain  level  of  safety  and  suitability,  and  the  GPT-4  model
          has  passed  the Turing  test. The  introduction  of AIGC  in  the  diagnosis  and  treatment  process  may  provide  technical  support  for  the
          rational use of clinical traditional Chinese medicine.
          KEYWORDS    GPT-4; traditional Chinese medicine prescription; generative artificial intelligence


              中医药作为中国传统文化的重要组成部分,在保障                         疾病预防、治疗和康复方面独具优势:中医药强调个体
          人民健康方面发挥着不可替代的作用。随着“健康中                            化辨证论治,可根据不同病因、病机和个体差异,制定有
          国”行动的深入推进,人民群众对健康美好生活需求的                           针对性的治疗方案;中医药还重视整体调理,通过调节
                                       [1]
          提升,中医药被赋予了更高的期望 。一方面,中医药在                          人体阴阳、气血等方式来提高机体免疫力,从而达到预
             Δ 基金项目 国家中医药管理局2022年宋纬文全国名老中医药专                 防疾病、延缓衰老、提高生活质量的目的。另一方面,中
          家传承工作室建设项目(No.国中医药人教函〔2022〕75号)                    医药产业也面临着巨大的发展机遇:当前,随着人民群
             *第一作者 药师。研究方向:药物制剂。电话:0598-8033609。
                                                             众对健康需求的提升,中医药市场需求不断增长;同时,
          E-mail:cqt1945@163.com
                                                             中医药在科技创新、标准化建设、产业升级等方面也取
             #  通信作者 主 任 中 药 师 。 研 究 方 向 :中 药 学 。 电 话 :0598-
          8033609。E-mail:869220642@qq.com                    得了重要进展,逐步实现了从传统到现代的转型升级,


          中国药房  2023年第34卷第23期                                              China Pharmacy  2023 Vol. 34  No. 23    · 2825 ·
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