输血医学中的大数据与红细胞质量控制的人工智能分析
Big Data in Transfusion Medicine and Artificial Intelligence Analysis for Red Blood Cell Quality Control.
作者信息
Lopes Marcelle G M, Recktenwald Steffen M, Simionato Greta, Eichler Hermann, Wagner Christian, Quint Stephan, Kaestner Lars
机构信息
Experimental Physics, Saarland University, Saarbrücken, Germany.
Cysmic GmbH, Saarbrücken, Germany.
出版信息
Transfus Med Hemother. 2023 May 25;50(3):163-173. doi: 10.1159/000530458. eCollection 2023 Jun.
BACKGROUND
"Artificial intelligence" and "big data" increasingly take the step from just being interesting concepts to being relevant or even part of our lives. This general statement holds also true for transfusion medicine. Besides all advancements in transfusion medicine, there is not yet an established red blood cell quality measure, which is generally applied.
SUMMARY
We highlight the usefulness of big data in transfusion medicine. Furthermore, we emphasize in the example of quality control of red blood cell units the application of artificial intelligence.
KEY MESSAGES
A variety of concepts making use of big data and artificial intelligence are readily available but still await to be implemented into any clinical routine. For the quality control of red blood cell units, clinical validation is still required.
背景
“人工智能”和“大数据”正日益从仅仅是有趣的概念迈向与我们的生活息息相关甚至成为生活一部分的阶段。这一普遍说法在输血医学领域同样适用。尽管输血医学取得了诸多进展，但目前尚未有一个普遍适用的成熟红细胞质量衡量标准。
总结
我们强调大数据在输血医学中的实用性。此外，我们以红细胞单位质量控制为例，强调人工智能的应用。
关键信息
利用大数据和人工智能的各种概念已 readily available（此处原文有误，推测是readily available，意为“现成可用”），但仍有待应用于任何临床常规操作中。对于红细胞单位的质量控制，仍需进行临床验证。
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