Bern University of Applied Sciences, Bern, Switzerland.
Harz University of Applied Sciences, Wernigerode, Germany.
Stud Health Technol Inform. 2023 Oct 20;309:43-47. doi: 10.3233/SHTI230736.
Transformer models have been successfully applied to various natural language processing and machine translation tasks in recent years, e.g. automatic language understanding. With the advent of more efficient and reliable models (e.g. GPT-3), there is a growing potential for automating time-consuming tasks that could be of particular benefit in healthcare to improve clinical outcomes. This paper aims at summarizing potential use cases of transformer models for future healthcare applications. Precisely, we conducted a survey asking experts on their ideas and reflections for future use cases. We received 28 responses, analyzed using an adapted thematic analysis. Overall, 8 use case categories were identified including documentation and clinical coding, workflow and healthcare services, decision support, knowledge management, interaction support, patient education, health management, and public health monitoring. Future research should consider developing and testing the application of transformer models for such use cases.
近年来，Transformer 模型已成功应用于各种自然语言处理和机器翻译任务，例如自动语言理解。随着更高效、更可靠的模型（例如 GPT-3）的出现，自动化耗时任务的潜力越来越大，这对于改善医疗保健临床结果可能特别有益。本文旨在总结 Transformer 模型在未来医疗保健应用中的潜在用例。具体来说，我们进行了一项调查，询问专家对未来用例的想法和思考。我们收到了 28 份回复，并使用经过改编的主题分析进行了分析。总的来说，确定了 8 个用例类别，包括文档和临床编码、工作流程和医疗保健服务、决策支持、知识管理、交互支持、患者教育、健康管理和公共卫生监测。未来的研究应该考虑开发和测试 Transformer 模型在这些用例中的应用。
