The exciting potential for ChatGPT in obstetrics and gynecology
The exciting potential for ChatGPT in obstetrics and gynecology
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DOI：
10.1016/j.ajog.2023.03.009
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发表时间：
2023-06-01
影响因子：
9.8
通讯作者：
Chervenak, Frank A.
中科院分区：
文献类型：
--
作者：
Grunebaum, Amos;Chervenak, Joseph;Chervenak, Frank A.
自然语言处理是人工智能的分支，主要研究计算机和人类语言之间的交互，近年来随着复杂的深度学习模型的引入，自然语言处理取得了显著的进步。自然语言处理任务（如文本和语音处理）的性能提高，为这些模型的能力提供了令人印象深刻的展示。到目前为止，也许没有任何演示比OpenAI在2022年11月推出的公开在线聊天机器人ChatGPT更具影响力，该机器人基于一种称为生成预训练Transformer的自然语言处理模型。通过作者向ChatGPT提出的一系列关于妇产科的问题作为提示，我们评估了模型处理临床相关查询的能力。它的回答表明，以目前的形式，ChatGPT对于那些想要获得该领域几乎任何主题的初步信息的用户来说都是有价值的。由于它的教育作用仍在界定中，我们必须认识到它的局限性。虽然答案一般都是雄辩的，知情的，并没有明显程度的错误或错误信息，我们也观察到它的弱点的证据。一个显著的缺点是，模型训练所依据的数据显然不容易更新。这里评估的特定模型似乎无法可靠地（如果有的话）获得2021年之后的数据。ChatGPT的用户希望数据更及时，需要注意这个缺点。无法引用来源或无法真正理解用户的问题表明它有误导的能力。负责任地使用像ChatGPT这样的模型对于确保它们能够帮助而不是伤害寻求妇产科信息的用户非常重要。
Natural language processing-the branch of artificial intelligence concerned with the interaction between computers and human language-has advanced markedly in recent years with the introduction of sophisticated deep-learning models. Improved performance in natural language processing tasks, such as text and speech processing, have fueled impressive demonstrations of these models' capabilities. Perhaps no demonstration has been more impactful to date than the introduction of the publicly available online chatbot ChatGPT in November 2022 by OpenAI, which is based on a natural language processing model known as a Generative Pretrained Transformer. Through a series of questions posed by the authors about obstetrics and gynecology to ChatGPT as prompts, we evaluated the model's ability to handle clinical-related queries. Its answers demonstrated that in its current form, ChatGPT can be valuable for users who want preliminary information about virtually any topic in the field. Because its educational role is still being defined, we must recognize its limitations. Although answers were generally eloquent, informed, and lacked a significant degree of mistakes or misinformation, we also observed evidence of its weaknesses. A significant drawback is that the data on which the model has been trained are apparently not readily updated. The specific model that was assessed here, seems to not reliably (if at all) source data from after 2021. Users of ChatGPT who expect data to be more up to date need to be aware of this drawback. An inability to cite sources or to truly understand what the user is asking suggests that it has the capability to mislead. Responsible use of models like ChatGPT will be important for ensuring that they work to help but not harm users seeking information on obstetrics and gynecology.