Natural language processing data services for healthcare providers.

IF 3.3 3区医学 Q2 MEDICAL INFORMATICS

BMC Medical Informatics and Decision Making Pub Date : 2024-11-26 DOI:10.1186/s12911-024-02713-x

Joshua Au Yeung, Anthony Shek, Thomas Searle, Zeljko Kraljevic, Vlad Dinu, Mart Ratas, Mohammad Al-Agil, Aleksandra Foy, Barbara Rafferty, Vitaliy Oliynyk, James T Teo

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引用次数: 0

Abstract

Purpose of review: Embedding machine learning workflows into real-world hospital environments is essential to ensure model alignment with clinical workflows and real-world data. Many non-healthcare industries undergoing digital transformation have already developed data labelling and data quality management services as a vertically integrated business process.

Recent findings: In this paper, we describe our experiences developing and implementing a first-of-its-kind clinical NLP (natural language processing) service in the National Health Service, United Kingdom using parallel harmonised platforms. We report on our work developing clinical NLP resources and implementation framework to distil expert clinical knowledge into our NLP models. To date, we have amassed over 26,086 annotations spanning 556 SNOMED CT concepts working with secondary care specialties. Our integrated language modelling service has delivered numerous clinical and operational use-cases using named entity recognition (NER). Such services improve efficiency of healthcare delivery and drive downstream data-driven technologies. We believe it will only be a matter of time before NLP services become an integral part of healthcare providers.

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为医疗保健提供商提供自然语言处理数据服务。

审查目的：将机器学习工作流程嵌入现实世界的医院环境中，对于确保模型与临床工作流程和现实世界的数据保持一致至关重要。许多正在进行数字化转型的非医疗行业已经开发了数据标注和数据质量管理服务，将其作为垂直整合的业务流程：在本文中，我们介绍了在英国国民健康服务中使用并行统一平台开发和实施同类首个临床 NLP（自然语言处理）服务的经验。我们报告了开发临床 NLP 资源的工作，以及将专家临床知识提炼到 NLP 模型中的实施框架。迄今为止，我们已积累了超过 26,086 个注释，涵盖 556 个 SNOMED CT 概念，并与二级医疗专科合作。我们的综合语言建模服务利用命名实体识别 (NER) 提供了大量临床和业务用例。此类服务提高了医疗保健服务的效率，并推动了下游数据驱动技术的发展。我们相信，NLP 服务成为医疗服务提供商不可或缺的一部分只是时间问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

BMC Medical Informatics and Decision Making 医学-医学：信息

CiteScore

7.20

自引率

5.70%

发文量

297

审稿时长

1 months

期刊介绍： BMC Medical Informatics and Decision Making is an open access journal publishing original peer-reviewed research articles in relation to the design, development, implementation, use, and evaluation of health information technologies and decision-making for human health.