Operationalizing and Implementing Pretrained, Large Artificial Intelligence Linguistic Models in the US Health Care System: Outlook of Generative Pretrained Transformer 3 (GPT-3) as a Service Model.
Operationalizing and Implementing Pretrained, Large Artificial Intelligence Linguistic Models in the US Health Care System: Outlook of Generative Pretrained Transformer 3 (GPT-3) as a Service Model.
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DOI：
10.2196/32875
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发表时间：
2022-02-10
影响因子：
3.2
通讯作者：
Linwood SL
中科院分区：
文献类型：
--
作者：
Sezgin E;Sirrianni J;Linwood SL
生成式预训练的Transformer模型由于其增强的功能和性能而最近很受欢迎。与许多现有的人工智能模型相比，生成式预训练的Transformer模型可以用非常有限的训练数据来执行。生成式预训练Transformer 3（GPT-3）是该管道中的最新版本之一，展示了对提示的类人逻辑和智能响应。一些例子包括写文章，回答复杂的问题，将代词与名词匹配，以及进行情感分析。然而，在医疗保健方面，特别是在临床实践和研究中的操作和使用方面，仍然存在问题。在这篇观点论文中，我们简要介绍了GPT-3及其功能，并通过一个用例概述了其在临床实践中的实施和操作的考虑因素。实施考虑因素包括（1）处理需求和信息系统基础设施，（2）运营成本，（3）模型偏差，以及（4）评估指标。此外，我们还概述了推动美国医疗保健系统采用GPT-3的三个主要操作因素：（1）确保遵守《健康保险携带和责任法案》，（2）与医疗保健提供者建立信任，以及（3）建立更广泛的GPT-3工具。这种观点可以告知医疗保健从业者，开发人员，临床医生和决策者了解集成到医院系统和医疗保健中的强大人工智能工具的使用。
Generative pretrained transformer models have been popular recently due to their enhanced capabilities and performance. In contrast to many existing artificial intelligence models, generative pretrained transformer models can perform with very limited training data. Generative pretrained transformer 3 (GPT-3) is one of the latest releases in this pipeline, demonstrating human-like logical and intellectual responses to prompts. Some examples include writing essays, answering complex questions, matching pronouns to their nouns, and conducting sentiment analyses. However, questions remain with regard to its implementation in health care, specifically in terms of operationalization and its use in clinical practice and research. In this viewpoint paper, we briefly introduce GPT-3 and its capabilities and outline considerations for its implementation and operationalization in clinical practice through a use case. The implementation considerations include (1) processing needs and information systems infrastructure, (2) operating costs, (3) model biases, and (4) evaluation metrics. In addition, we outline the following three major operational factors that drive the adoption of GPT-3 in the US health care system: (1) ensuring Health Insurance Portability and Accountability Act compliance, (2) building trust with health care providers, and (3) establishing broader access to the GPT-3 tools. This viewpoint can inform health care practitioners, developers, clinicians, and decision makers toward understanding the use of the powerful artificial intelligence tools integrated into hospital systems and health care.
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影响因子：
15.2
作者：
Korngiebel DM;Mooney SD
通讯作者：
Mooney SD
影响因子：
15.2
作者：
Sadilek A;Liu L;Nguyen D;Kamruzzaman M;Serghiou S;Rader B;Ingerman A;Mellem S;Kairouz P;Nsoesie EO;MacFarlane J;Vullikanti A;Marathe M;Eastham P;Brownstein JS;Arcas BAY;Howell MD;Hernandez J
通讯作者：
Hernandez J
影响因子：
15.2
作者：
McGraw D;Mandl KD
通讯作者：
Mandl KD
影响因子：
2.1
作者：
Watson, Joshua;Hutyra, Carolyn A.;Poon, Eric G.
通讯作者：
Poon, Eric G.