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医学信息学研究入门的十个主题

Ten Topics to Get Started in Medical Informatics Research.

机构信息

Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.

Center for Scalable Data Analytics and Artificial Intelligence, Dresden, Germany.

出版信息

J Med Internet Res. 2023 Jul 24;25:e45948. doi: 10.2196/45948.

Abstract

The vast and heterogeneous data being constantly generated in clinics can provide great wealth for patients and research alike. The quickly evolving field of medical informatics research has contributed numerous concepts, algorithms, and standards to facilitate this development. However, these difficult relationships, complex terminologies, and multiple implementations can present obstacles for people who want to get active in the field. With a particular focus on medical informatics research conducted in Germany, we present in our Viewpoint a set of 10 important topics to improve the overall interdisciplinary communication between different stakeholders (eg, physicians, computational experts, experimentalists, students, patient representatives). This may lower the barriers to entry and offer a starting point for collaborations at different levels. The suggested topics are briefly introduced, then general best practice guidance is given, and further resources for in-depth reading or hands-on tutorials are recommended. In addition, the topics are set to cover current aspects and open research gaps of the medical informatics domain, including data regulations and concepts; data harmonization and processing; and data evaluation, visualization, and dissemination. In addition, we give an example on how these topics can be integrated in a medical informatics curriculum for higher education. By recognizing these topics, readers will be able to (1) set clinical and research data into the context of medical informatics, understanding what is possible to achieve with data or how data should be handled in terms of data privacy and storage; (2) distinguish current interoperability standards and obtain first insights into the processes leading to effective data transfer and analysis; and (3) value the use of newly developed technical approaches to utilize the full potential of clinical data.

摘要

临床中不断产生的大量异质数据可以为患者和研究人员带来巨大的财富。医学信息学研究领域的快速发展为促进这一发展贡献了许多概念、算法和标准。然而,这些复杂的关系、复杂的术语和多种实现方式可能会给那些希望涉足该领域的人带来障碍。我们特别关注在德国进行的医学信息学研究,在我们的观点中提出了 10 个重要主题,以改善不同利益相关者(例如医生、计算专家、实验人员、学生、患者代表)之间的整体跨学科交流。这可能会降低进入门槛,并为不同层次的合作提供起点。我们简要介绍了建议的主题,然后提供了一般最佳实践指导,并推荐了深入阅读或实践教程的其他资源。此外,这些主题旨在涵盖医学信息学领域的当前方面和开放的研究空白,包括数据法规和概念、数据协调和处理以及数据评估、可视化和传播。此外,我们还提供了一个如何将这些主题集成到高等教育医学信息学课程中的示例。通过认识到这些主题,读者将能够:(1)将临床和研究数据置于医学信息学的背景下,了解通过数据可以实现什么,或者在数据隐私和存储方面应该如何处理数据;(2)区分当前的互操作性标准,并初步了解导致有效数据传输和分析的过程;(3)重视使用新开发的技术方法来充分利用临床数据的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8be4/10407648/6b8f5d8a556b/jmir_v25i1e45948_fig1.jpg

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