DataTools4Heart: A European Health Data Toolbox for Enhancing Cardiology Data Interoperability, Reusability and Privacy

心血管疾病（CVD）仍然是全世界死亡的主要原因，约占每年死亡人数的三分之一。重复使用结构化和非结构化数据有可能为心血管疾病患者带来重大健康益处。欧洲的医疗保健数据重用面临隐私和碎片化问题、数据格式和语言的高度多样性，以及缺乏技术和临床互操作性。DataTools4Heart （DT4H）将解决这些挑战，并开发一个全面、联合、保护隐私的心脏病学数据工具箱。这将包括，在一个集成平台中，提供通用数据模型的标准化数据摄取和协调工具，多语言自然语言处理，联邦机器学习，差异私有数据合成生成，以及适应心脏病学领域的7种语言模型。DT4H虚拟助手将帮助科学家和临床医生浏览大规模的多源心脏病学数据。这些工具的实施将：i)确保隐私设计，并完全符合欧洲法规和数据标准；Ii)基于多利益相关方以用户为中心的需求进行优化；iii)在欧洲7个临床站点进行验证。DT4H将解锁非结构化数据中当前无法访问的健康数据，并允许多站点联合数据使用。与它的工具箱一起，DT4H将留下一个具有嵌入式元数据目录和人工智能虚拟助手的联合学习平台的遗产，以及CardioSynth合成数据开放数据库，以供进一步研究和人工智能实验使用。有效利用联合学习平台将使改进的人工智能诊断和治疗工具成为可能。部署受监管的解决方案将扩展现有的医疗保健管理范例，以减轻疾病负担。最后，DT4H工具、系统和方法是高度一般化的，将很好地转化为医学的其他临床和研究领域。

Cardiovascular disease (CVD) remains the main cause of mortality worldwide, accounting for about a third of annual deaths. Re-use of both structured and unstructured data has the potential for major health benefits for the population suffering from CVD. Healthcare data re-use in Europe faces privacy and fragmentation issues, a high diversity in data formats and languages, and a lack of technical and clinical interoperability. DataTools4Heart (DT4H) will tackle such challenges and develop a comprehensive, federated, privacypreserving cardiology data toolbox. This will include, in an integrated platform, standardised data ingestion and harmonisation tools providing a common data model, multilingual natural language processing, federated machine learning, differentially private data synthesis generation, and 7 language models adapted to the cardiology domain. DT4H virtual assistants will help scientists and clinicians navigate through large-scale multi-source cardiology data. These tools will be: i) implemented ensuring privacy-by-design and thorough compliance with European regulations and data standards; ii) optimised as based on multi-stakeholder user-centred requirements; and, iii) validated in 7 clinical sites across Europe. DT4H will unlock currently inaccessible health data in unstructured data and allow multisite federated data use. Together with itstoolbox, DT4H will leave the legacy of a federated learning platform with an embedded metadata catalogue and AI virtual assistants, and the CardioSynth open database of synthetic data remaining as available for further research and AI experimentation. Effective use of the federated learning platform will improve enable improved AI diagnostic and treatment tools. Deployment of regulated solutions will extend existing healthcare management paradigms to reduce disease burden. Finally, DT4H tools, systems and methodology are highly generalised and will translate well to other clinical and research areas in medicine.