摘要
传统生物医学数据分析技术在大数据时代背景下,面临着巨大挑战,而深度学习技术在生物医学分析领域的应用,迎来了巨大的发展机遇。本文综述了深度学习在生物医学数据分析领域的最新研究进展。首先阐述了深度学习方法及工具,随后以时间为主线,围绕生物医学问题的提出、数据预处理方法、模型建立方法、训练算法重点总结了近五年深度学习在生物医学数据分析中的具体应用,并重点强调了医疗辅助诊断中的深度学习应用。最后给出了未来深度学习在生物医学数据分析领域可能的发展方向。
Traditional biomedical data analysis technology faces enormous challenges in the context of the big data era. The application of deep learning technology in the field of biomedical analysis has ushered in tremendous development opportunities. In this paper, we reviewed the latest research progress of deep learning in the field of biomedical data analysis. Firstly, we introduced the deep learning method and its common framework. Then, focusing on the proposal of biomedical problems, data preprocessing method, model building method and training algorithm, we summarized the specific application of deep learning in biomedical data analysis in the past five years according to the chronological order, and emphasized the application of deep learning in medical assistant diagnosis. Finally, we gave the possible development direction of deep learning in the field of biomedical data analysis in the future.
作者
李肃义
唐世杰
李凤
齐建卓(综述)
熊文激(审校)
LI Suyi;TANG Shijie;LI Feng;QI Jianzhuo;XIONG Wenji(College of Instrumentation and Electrical Engineering,Jilin University,Changchun 130061,P.R.China;Xining No.1 People's Hospital,Xining 810000,P.R.China;The First Hospital of Jilin University,Changchun 130021,P.R.China)
出处
《生物医学工程学杂志》
EI
CAS
CSCD
北大核心
2020年第2期349-357,共9页
Journal of Biomedical Engineering
基金
国家重点技术研发计划(2017YFC0307700)
吉林省国家自然科学基金项目(20180101049JC)。
关键词
深度学习
生物医学
数据分析
deep learning
biomedical science
data analysis
