| 基于机器学习的医疗大数据分析与临床应用 |
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| 引用本文： | 孙 涛,徐秀林.基于机器学习的医疗大数据分析与临床应用[J].教育技术导刊,2019,18(11):10-14. |
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| 作者姓名： | 孙 涛 徐秀林 |
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| 作者单位： | 上海理工大学 医疗器械与食品学院，上海 200093 |
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| 摘 要： | 医疗大数据指数目庞大、增长迅速、结构复杂、隐藏价值高的数据。机器学习技术能够有效分析医疗大数据的内部联系，对疾病的早期诊断及预后具有重要临床指导意义。阐述了机器学习技术在医疗大数据中的应用及研究进展，包括在大数据分析中的回归分析、决策树、基于内核的算法、降低维度算法等浅层机器学习算法模型，卷积神经网络、循环神经网络、自动编码器、深度信念网络等深度学习算法模型，以及各个算法模型的临床应用，分析了机器学习在医疗数据挖掘中的应用前景和存在的技术难题。
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| 关 键 词： | 医疗大数据 机器学习 诊断及预后 深度学习 临床应用 |
| 收稿时间： | 2019-01-07 |
Medical Big Data Analysis and Clinical Application Based on Machine Learning |
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| SUN Tao,XU Xiu-lin.Medical Big Data Analysis and Clinical Application Based on Machine Learning[J].Introduction of Educational Technology,2019,18(11):10-14. |
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| Authors: | SUN Tao XU Xiu-lin |
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| Institution: | College of Medical Devices and Food， Shanghai University of Science and Technology，Shanghai 200093，China |
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| Abstract: | Medical big data is a kind of data with huge amount， rapid growth， complex structure and high hidden value. Machine learning （ML） technology can effectively analyze and interpret the internal relations of medical big data， and has important clinical guiding significance in the early diagnosis and prognosis of diseases. This article expounds the machine learning technology in the medical application of big data and its research progress， including the analysis of large data in regression analysis， decision tree， based on the kernel algorithm， to reduce the dimension of the shallow machine learning algorithms， circulating neural network model and the convolution neural network， the automatic encoder， deep deep learning algorithms such as belief network model and the clinical application of each algorithm model， the medical application prospect of machine learning and the existing technical problems in data mining are analyzed. |
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| Keywords: | medical big data machine learning diagnosis and prognosis deep learning clinical application |
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