Koru Güneş
Department of Health Policy and Management University of Arkansas for Medical Sciences (UAMS) Fayetteville Arkansas USA.
Department of Biomedical Informatics University of Arkansas for Medical Sciences (UAMS) Fayetteville Arkansas USA.
Learn Health Syst. 2023 Oct 5;7(4):e10396. doi: 10.1002/lrh2.10396. eCollection 2023 Oct.
Computable biomedical knowledge artifacts (CBKs) are software programs that transform input data into practical output. CBKs are expected to play a critical role in the future of learning health systems. While there has been rapid growth in the development of CBKs, broad adoption is hampered by limited verification, documentation, and dissemination channels. To address these issues, the Learning Health Systems journal created a track dedicated to publishing CBKs through a peer-review process. Peer review of CBKs should improve reproducibility, reuse, trust, and recognition in biomedical fields, contributing to learning health systems. This special issue introduces the CBK track with four manuscripts reporting a functioning CBK, and another four manuscripts tackling methodological, policy, deployment, and platform issues related to fostering a healthy ecosystem for CBKs. It is our hope that the potential of CBKs exemplified and highlighted by these quality publications will encourage scientists within learning health systems and related biomedical fields to engage with this new form of scientific discourse.
可计算生物医学知识工件（CBK）是将输入数据转换为实际输出的软件程序。预计CBK将在学习型健康系统的未来发挥关键作用。虽然CBK的开发一直在迅速增长，但广泛采用受到验证、文档和传播渠道有限的阻碍。为了解决这些问题，《学习健康系统》杂志设立了一个专栏，专门通过同行评审过程发表CBK。对CBK的同行评审应提高生物医学领域的可重复性、可重用性、可信度和认可度，为学习型健康系统做出贡献。本期特刊通过四篇报告功能正常的CBK的手稿以及另外四篇解决与促进CBK健康生态系统相关的方法、政策、部署和平台问题的手稿介绍了CBK专栏。我们希望这些高质量出版物所例证和突出的CBK的潜力将鼓励学习型健康系统和相关生物医学领域的科学家参与这种新的科学话语形式。
