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Construction of databases:advances and significance in clinical research 被引量:1
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作者 erping long Bingjie Huang +2 位作者 Liming Wang Xiaoyu Lin Haotian Lin 《Eye Science》 CAS 2015年第4期184-189,共6页
Widely used in clinical research, the database is a new type of data management automation technology and the most efficient tool for data management. In this article, we first explain some basic concepts, such as the... Widely used in clinical research, the database is a new type of data management automation technology and the most efficient tool for data management. In this article, we first explain some basic concepts, such as the definition, classification, and establishment of databases. Afterward, the workflow for establishing databases, inputting data, verifying data, and managing databases is presented. Meanwhile, by discussing the application of databases in clinical research, we illuminate the important role of databases in clinical research practice. Lastly, we introduce the reanalysis of randomized controlled trials(RCTs) and cloud computing techniques, showing the most recent advancements of databases in clinical research. 展开更多
关键词 数据库建设 临床 随机对照试验 数据管理 自动化技术 管理数据库 输入数据 工作流程
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Handwashing quality assessment via deep learning:a modelling study for monitoring compliance and standards in hospitals and communities
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作者 Ting Wang Jun Xia +9 位作者 Tianyi Wu Huanqi Ni erping long Ji-Peng Olivia Li Lanqin Zhao Ruoxi Chen Ruixin Wang Yanwu Xu Kai Huang Haotian Lin 《Intelligent Medicine》 2022年第3期152-160,共9页
Background Hand hygiene can be a simple,inexpensive,and effective method for preventing the spread of infectious diseases.However,a reliable and consistent method for monitoring adherence to the guidelines within and ... Background Hand hygiene can be a simple,inexpensive,and effective method for preventing the spread of infectious diseases.However,a reliable and consistent method for monitoring adherence to the guidelines within and outside healthcare settings is challenging.The aim of this study was to provide an approach for monitoring handwashing compliance and quality in hospitals and communities.Methods We proposed a deep learning algorithm comprising three-dimensional convolutional neural networks(3D CNNs)and used 230 standard handwashing videos recorded by healthcare professionals in the hospital or at home for training and internal validation.An assessment scheme with a probability smoothing method was also proposed to optimize the neural network’s output to identify the handwashing steps,measure the exact duration,and grade the standard level of recognized steps.Twenty-two videos by healthcare professionals in another hospital and 28 videos recorded by civilians in the community were used for external validation.Results Using a deep learning algorithm and an assessment scheme,combined with a probability smoothing method,each handwashing step was recognized(ACC ranged from 90.64%to 98.87%in the hospital and from 87.39%to 96.71%in the community).An assessment scheme measured each step’s exact duration,and the intraclass correlation coefficients were 0.98(95%CI:0.97-0.98)and 0.91(95%CI:0.88-0.93)for the total video duration in the hospital and community,respectively.Furthermore,the system assessed the quality of handwashing,similar to the expert panel(kappa=0.79 in the hospital;kappa=0.65 in the community).Conclusions This work developed an algorithm to directly assess handwashing compliance and quality from videos,which is promising for application in healthcare settings and communities to reduce pathogen transmis-sion. 展开更多
关键词 HANDWASHING Infectious control Deep learning Action recognition Standard level grading
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