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1.
死亡风险预测指根据病人临床体征监测数据来预测未来一段时间的死亡风险。对于ICU病患,通过死亡风险预测可以有针对性地对病人做出临床诊断,以及合理安排有限的医疗资源。基于临床使用的MEWS和Glasgow昏迷评分量表,针对ICU病人临床监测的17项生理参数,提出一种基于多通道的ICU脑血管疾病死亡风险预测模型。引入多通道概念应用于BiLSTM模型,用于突出每个生理参数对死亡风险预测的作用。采用Attention机制用于提高模型预测精度。实验数据来自MIMIC [Ⅲ]数据库,从中提取3?080位脑血管疾病患者的16?260条记录用于此次研究,除了六组超参数实验之外,将所提模型与LSTM、Multichannel-BiLSTM、逻辑回归(logistic regression)和支持向量机(support vector machine, SVM)四种模型进行了对比分析,准确率Accuracy、灵敏度Sensitive、特异性Specificity、AUC-ROC和AUC-PRC作为评价指标,实验结果表明,所提模型性能优于其他模型,AUC值达到94.3%。 相似文献
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Aishwarya
Srivastava Siddhant Aggarwal Amy Apon Edward Duffy Ken Kennedy Andre Luckow Brandon Posey Marcin Ziolkowski 《Software》2020,50(6):868-898
We investigate the challenges of building an end-to-end cloud pipeline for real-time intelligent visual inspection system for use in automotive manufacturing. Current methods of visual detection in automotive assembly are highly labor intensive, and thus prone to errors. An automated process is sought that can operate within the real-time constraints of the assembly line and can reduce errors. Components of the cloud pipeline include capture of a large set of high-definition images from a camera setup at the assembly location, transfer and storage of the images as needed, execution of object detection, and notification to a human operator when a fault is detected. The end-to-end execution must complete within a fixed time frame before the next car arrives in the assembly line. In this article, we report the design, development, and experimental evaluation of the tradeoffs of performance, accuracy, and scalability for a cloud system. 相似文献
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Train driving is a highly visual task. The visual capabilities of the train driver affects driving safety and driving performance. Understanding the effects of train speed and background image complexity on the visual behavior of the high-speed train driver is essential for optimizing performance and safety. This study investigated the role of the apparent image velocity and complexity on the dynamic visual field of drivers. Participants in a repeated-measures experiment drove a train at nine different speeds in a state-of-the-art high-speed train simulator. Eye movement analysis indicated that the effect of image velocity on the dynamic visual field of high-speed train driver was significant while image complexity had no effect on it. The fixation range was increasingly concentrated on the middle of the track as the speed increased, meanwhile there was a logarithmic decline in fixation range for areas surrounding the track. The extent of the visual search field decreased gradually, both vertically and horizontally, as the speed of train increased, and the rate of decrease was more rapid in the vertical direction. A model is proposed that predicts the extent of this tunnel vision phenomenon as a function of the train speed.Relevance to industryThis finding can be used as a basis for the design of high-speed railway system and as a foundation for improving the operational procedures of high-speed train driver for safety. 相似文献
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随着社交媒体的发展,用户之间的关系网络对于社交媒体的分析有很大的帮助。因此,该文主要研究用户好友关系检测。以往的关于用户好友关系抽取的研究主要基于社交媒体上的结构化信息,比如其他好友关系,用户的不同属性等。但是,很多时候用户本身并没有大量的好友信息存在,同时也不一定有很多确定的属性。因此,我们希望基于用户发表的文本信息来对用户关系进行预测。不同于以往的潜在好友推荐算法,该文提出了一种基于注意力机制以及长短时记忆网络(long short-term memory,LSTM)的好友关系预测模型,将好友之间的评论分开处理,通过分析用户之间的评论来判断是否具备一定的好友关系。该模型将好友双方信息拼接后的结果作为输入,并将注意力机制应用于LSTM的输出。实验表明,用户之间的评论对于好友关系预测确实有较大的实际意义,该文提出的模型较之于多个基准系统的效果,取得了明显的提升。在不加入任何其它非文本特征的情况下,实验结果的准确率达到了77%。 相似文献
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This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning
of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed
Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given
visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample
size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive
experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr
and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood
(ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given
sparse data, while CL-AIC should be chosen given moderate or large data sample sizes. 相似文献
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浅谈如何有效学习计算机软件知识 总被引:1,自引:0,他引:1
黄霞 《湖南工业职业技术学院学报》2003,3(2):79-80
计算机软件知识的学习并不是完全线性的,而是不断循环往复、迭代的过程。本对如何深入、广泛、有效地学习计算机软件知识做出了一些探讨。 相似文献
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Barch Deanna M.; Mitropoulou Vivian; Harvey Philip D.; New Antonia S.; Silverman Jeremy M.; Siever Larry J. 《Canadian Metallurgical Quarterly》2004,113(4):556
Research suggests that schizotypal personality disorder (SPD) is a part of the spectrum of schizophrenia-related illnesses. This article hypothesizes that a deficit in the representation and maintenance of context is a core cognitive disturbance in schizophrenia and that SPD individuals should demonstrate context-processing deficits. To test this hypothesis, the authors administered 3 versions of their AX-CPT task, designed to assess context processing, to 35 healthy controls and 26 individuals with DSM-IV SPD. They also administered working memory and selective attention tasks. SPD individuals displayed context representation deficits similar to those found in schizophrenia but did not show the same additional deficits in context maintenance. Context processing was strongly associated with working memory and selective attention performance in the SPD individuals. (PsycINFO Database Record (c) 2010 APA, all rights reserved) 相似文献
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