基于认知计算的CDSS在医疗实践中的应用

Health data science Pub Date : 2021-07-22 eCollection Date: 2021-01-01 DOI:10.34133/2021/9819851
Jun Chen, Chao Lu, Haifeng Huang, Dongwei Zhu, Qing Yang, Junwei Liu, Yan Huang, Aijun Deng, Xiaoxu Han
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引用次数: 0

摘要

重要性过去十年见证了认知计算技术的进步,这些技术在医学研究中具有规模和目的地进行学习。从疾病诊断到治疗计划的制定,认知计算包括数据驱动和知识驱动的机器智能,以帮助医疗保健在临床决策中发挥作用。这篇综述从过去十年中基于认知计算的CDSS的研究和工业努力提供了一个全面的视角。亮点。(1) 对基于认知计算的CDSS的研究论文和行业实践进行了全面回顾,以确定构建该系统的必要性、特点以及总体框架。(2) 在通用框架下,详细介绍了基于认知计算的CDSS的几个典型应用以及现有系统在实际医疗实践中的应用。(3) 讨论了当前基于认知计算的CDSS的局限性,为未来在这一方向上的工作提供了启示。结论与医疗内容提供商不同,基于认知计算的CDSS通过从医疗大数据中自动学习和推理,提供概率临床决策支持。管理多模态数据和计算机化医学知识的特点将基于认知计算的CDSS与其他类别区分开来。鉴于初级卫生保健的现状,如诊断错误率高和医疗资源短缺,现在是时候将基于认知计算的CDSS引入医学界了,医学界应该更加开放,接受基于认知计算CDSS带来的便利性和低成本但高效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cognitive Computing-Based CDSS in Medical Practice.

Importance. The last decade has witnessed the advances of cognitive computing technologies that learn at scale and reason with purpose in medicine studies. From the diagnosis of diseases till the generation of treatment plans, cognitive computing encompasses both data-driven and knowledge-driven machine intelligence to assist health care roles in clinical decision-making. This review provides a comprehensive perspective from both research and industrial efforts on cognitive computing-based CDSS over the last decade.Highlights. (1) A holistic review of both research papers and industrial practice about cognitive computing-based CDSS is conducted to identify the necessity and the characteristics as well as the general framework of constructing the system. (2) Several of the typical applications of cognitive computing-based CDSS as well as the existing systems in real medical practice are introduced in detail under the general framework. (3) The limitations of the current cognitive computing-based CDSS is discussed that sheds light on the future work in this direction.Conclusion. Different from medical content providers, cognitive computing-based CDSS provides probabilistic clinical decision support by automatically learning and inferencing from medical big data. The characteristics of managing multimodal data and computerizing medical knowledge distinguish cognitive computing-based CDSS from other categories. Given the current status of primary health care like high diagnostic error rate and shortage of medical resources, it is time to introduce cognitive computing-based CDSS to the medical community which is supposed to be more open-minded and embrace the convenience and low cost but high efficiency brought by cognitive computing-based CDSS.

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