摘要
随着机器学习技术的广泛应用,深度学习作为一个新兴分支,由于其自动特征学习与函数模拟构建方面的优势,在图像识别、自然语言处理等领域取得了不菲成绩。为了解深度学习在生物医学领域的研究进展,本文通过文献调研的方法,对深度学习在该方向相关成果进行研究分析。研究发现,深度学习在该领域的应用主要集中在生物信息学、医学图像识别、病症预测、临床辅助决策和药物开发等方面,已有研究通过将该领域的文字、图像、信号等记录信息进行多维量化,利用深度学习开发多种模型进行数据特征学习、信息挖掘、状态模拟,完成了识别、评价、预测等功能。深度学习凭借其复杂模拟算法的优势,在生物医学领域的实践取得了优于传统算法的成果,并且在疾病自动编码、多数据源整合分析、公共卫生领域等方面的应用实践值得进一步探索。
With the wide application of machine learning technology,deep learning has achieved a lot as an emerging branch of machine learning.Due to its advantages in automatic feature learning and function simulation construction,deep learning has made great contributions in the fields of image recognition and natural language processing.To understand the existing research progress of deep learning in the field of biomedicine,this paper studies the related achievements of deep learning in this field through literature investigation.It is found that the application of deep learning in this field mainly focuses on bioinformatics,medical image recognition,disease prediction,clinical assisted decision-making and drug development,etc.There have been studies that transform information such as texts,images,and signals into multi-dimensional vectors.These studies use deep learning to develop a variety of models that are capable of learning data features,mining information and simulating status,so as to realize identification,evaluation,prediction and some other functions.With its advantages of complex simulation algorithms,deep learning has achieved better results than traditional algorithms in the field of biomedicine,and its application in areas such as automatic disease coding,integrated analysis of multiple data sources,and public health are worthy of further exploration.
作者
朱冬亮
文奕
陶欣
ZHU Dongliang;WEN Yi;TAO Xin(Chengdu Library and Information Center,Chinese Academy of Sciences,Chengdu 610041,China;Department of Library,Information and Archi ves Management,School of Economics and Management,University of Chinese Academy of Sciences,Beijing 100864,China;The Foundation For Embryonic Competence,Basking Ridge 07920,USA)
出处
《世界科技研究与发展》
CSCD
2020年第5期510-519,共10页
World Sci-Tech R&D
基金
2019-2020年院文献情报能力专项(Y9290002-3.5.3)。
关键词
深度学习
机器学习
生物医药
医学
Deep Learning
Machine Learning
Biomedicine
Medicine
