Research and application of deep learning in laboratory medicine

Q4 Health Professions 中华检验医学杂志 Pub Date : 2019-12-11 DOI:10.3760/CMA.J.ISSN.1009-9158.2019.12.016
Hong Yan, Guoye Liu, Yan Li, Rui Xia, Qian Wang, Chengbin Wang
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引用次数: 2

Abstract

In the context of the rapid development of big data in the healthcare field, deep learning (DL), as a machine learning algorithm that provides a more flexible solution for image and speech recognition as well as natural language processing, has the ability to extract important information from medical data into valuable knowledge and it has received unprecedented attention in many real-world tasks. This paper briefly introduces common network structure of deep learning and its latest research progress in the field of medical laboratory. In addition, this review also exploreed some of the inherent challenges and prospective research directions about deep learning that affecting in the medical laboratory. Key words: Deep learning; Big data; Medical laboratory
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深度学习在检验医学中的研究与应用
在医疗领域大数据快速发展的背景下,深度学习(deep learning, DL)作为一种机器学习算法,能够将医疗数据中的重要信息提取为有价值的知识,为图像和语音识别以及自然语言处理提供了更加灵活的解决方案,在许多现实世界的任务中受到了前所未有的关注。本文简要介绍了深度学习常用的网络结构及其在医学实验室领域的最新研究进展。此外,本文还探讨了深度学习在医学实验室中面临的一些内在挑战和未来的研究方向。关键词:深度学习;大数据;医学实验室
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来源期刊
中华检验医学杂志
中华检验医学杂志 Health Professions-Medical Laboratory Technology
CiteScore
0.40
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0.00%
发文量
8037
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