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A study on specialist or special disease clinics based on big data

Zhuyuan Fang,Xiaowei Fan,Gong Chen

Frontiers of Medicine 2014, Volume 8, Issue 3, Pages 376-381 doi: 10.1007/s11684-014-0356-9

Abstract:

Correlation analysis and processing of massive medical information can be implemented through bigThis paper explores the concept of constructing a big medical data platform and introduces the clinicalMedical data can be collected and consolidated by distributed computing technology.Through analysis technology, such as artificial neural network and grey model, a medical model can beBig data analysis, such as Hadoop, can be used to construct early prediction and intervention models

Keywords： big data correlation analysis medical information integration data analysis clinical model

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Slope stability analysis based on big data and convolutional neural network

Yangpan FU; Mansheng LIN; You ZHANG; Gongfa CHEN; Yongjian LIU

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 7, Pages 882-895 doi: 10.1007/s11709-022-0859-4

Abstract: A CNN model can process data quickly and complete a large amount of data analysis in a specific situationIt is difficult to get enough slope data samples in practical engineering.Moreover, the prediction accuracy of the CNN trained by the sample database for slope stability analysisIn particular, the combination of typical actual slopes and generated slope data provides enough training

Keywords： slope stability limit equilibrium method convolutional neural network database for slopes big data

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Special issue: Innovative applications of big data and artificial intelligence

Frontiers of Engineering Management 2022, Volume 9, Issue 4, Pages 517-519 doi: 10.1007/s42524-022-0234-0

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A review of systematic evaluation and improvement in the big data environment

Feng YANG, Manman WANG

Frontiers of Engineering Management 2020, Volume 7, Issue 1, Pages 27-46 doi: 10.1007/s42524-020-0092-6

Abstract: The era of big data brings unprecedented opportunities and challenges to management research.Exploring the applicable evaluation methods in the big data environment has become an important subjectdata environment.We first review the evaluation methods based on the main analytic techniques of big data such as dataFocused on the characteristics of big data (association feature, data loss, data noise, and visualization

Keywords： big data evaluation methods systematic improvement big data analytic techniques data mining

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Challenges to Engineering Management in the Big Data Era

Yong Shi

Frontiers of Engineering Management 2015, Volume 2, Issue 3, Pages 293-303 doi: 10.15302/J-FEM-2015042

Abstract: This paper presents a review of the challenges to engineering management in the Big Data Era as wellas the Big Data applications.First, it outlines the definitions of big data, data science and intelligent knowledge and the historyof big data.Second, the paper reviews the academic activities about big data in China.

Keywords： big data data science intelligent knowledge engineering management real-life applications

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Clinical research of traditional Chinese medicine in big data era

Junhua Zhang,Boli Zhang

Frontiers of Medicine 2014, Volume 8, Issue 3, Pages 321-327 doi: 10.1007/s11684-014-0370-y

Abstract:

With the advent of big data era, our thinking, technology and methodology are being transformed.Data-intensive scientific discovery based on big data, named “The Fourth Paradigm,” has becomeof diagnosis and treatment, and genomic data have been accumulated dramatically, which generates bigTo conduct clinical studies involved in big data in TCM domain, top level design is needed and shouldcreation, data analysis technology and big-data professionals fostering and training.

Keywords： big data traditional Chinese medicine clinical evaluation evidence based medicine

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Appreciating the role of big data in the modernization of environmental governance

Frontiers of Engineering Management 2022, Volume 9, Issue 1, Pages 163-169 doi: 10.1007/s42524-021-0185-x

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Application of Big Data Analysis Methods for Technology Foresight in Strategic Emerging Industries

Liu Yufei, Zhou Yuan, Liao Ling

Strategic Study of CAE 2016, Volume 18, Issue 4, Pages 121-128 doi: 10.15302/J-SSCAE-2016.04.018

Abstract: Delphi expert analysis is currently the most popular method for technology foresight.This method is undermined by a lack of reliabe and valid big data to support expert experience.The authors propose a new method for patent and technical document analysis for the use of technology

Keywords： technology foresight bibliometric patent analysis big data analysis emerging industry

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Scientific computation of big data in real-world clinical research

Guozheng Li,Xuewen Zuo,Baoyan Liu

Frontiers of Medicine 2014, Volume 8, Issue 3, Pages 310-315 doi: 10.1007/s11684-014-0358-7

Abstract:

The advent of the big data era creates both opportunities and challenges for traditional Chinese medicinefeature subset optimizing, multi-label learning, and complex networks based on complexity, intelligence, dataFurthermore, these methods are applied in the modeling and analysis of the various complex relationships

Keywords： big data real world clinical research Chinese medicine medical computing

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Study on Big Data-based Behavior Modification in Metro Construction

Lie-yun Ding,Sheng-yu Guo

Frontiers of Engineering Management 2015, Volume 2, Issue 2, Pages 131-136 doi: 10.15302/J-FEM-2015037

Abstract: This paper introduces the study on big data-based metro construction behavior modification, aiming to

Keywords： big data unsafe behavior behavior modification behavior-based safety (BBS) unsafe behavior rate

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Utilizing big data to build personalized technology and system of diagnosis and treatment in traditional

Baoyan Liu

Frontiers of Medicine 2014, Volume 8, Issue 3, Pages 272-278 doi: 10.1007/s11684-014-0364-9

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A neural network-based production process modeling and variable importance analysis approach in corn

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 3, Pages 358-371 doi: 10.1007/s11705-022-2190-y

Abstract: Big data technology provides a promising solution as its ability to turn huge amounts of data into insightsIn this paper, a neural network-based production process modeling and variable importance analysis approachis proposed for corn to sugar processes, which contains data preprocessing, dimensionality reductionLASSO analysis is first applied to reduce the data dimension to 155, then the inputs are dimensionalizedUltimately, variable importance analysis is carried out by the extended weight connection method, and

Keywords： big data corn to sugar factory neural network variable importance analysis

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Big Data to support sustainable urban energy planning: The EvoEnergy project

Moulay Larbi CHALAL, Benachir MEDJDOUB, Nacer BEZAI, Raid SHRAHILY

Frontiers of Engineering Management 2020, Volume 7, Issue 2, Pages 287-300 doi: 10.1007/s42524-019-0081-9

Abstract: consumption where we developed a 3D urban energy prediction system (EvoEnergy) using the old UK panel datasurvey, namely, the British household panel data survey (BHPS).The analysis of the results advised that EvoEnergy remains a reliable prediction system and had a goodprediction accuracy (MAPE  5%) when compared to actual energy performance certificate data., to consider merging the BHPS and UKHLS data sets.

Keywords： urban energy planning sustainable planning Big Data household transition energy prediction

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IN2CLOUD: A novel concept for collaborative management of big railway data

Jing LIN, Uday KUMAR

Frontiers of Engineering Management 2017, Volume 4, Issue 4, Pages 428-436 doi: 10.15302/J-FEM-2017048

Abstract: Shift2Rail Multi-Annual Action Plan, the challenge of railway maintenance is generating knowledge from dataan intelligent cloud with hybrid cloud learning, and 3) collaborative management using asset-related datalearn from each other (including domain knowledge and experience) but do not want to share their raw data

Keywords： railway intelligent asset management collaborative learning big data hybrid cloud Bayesian

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Big data and machine learning: A roadmap towards smart plants

Frontiers of Engineering Management Pages 623-639 doi: 10.1007/s42524-022-0218-0

Abstract: components are smart sensing, mobile communication, Internet of Things, modelling and simulation, advanced dataprocessing, storage and analysis, advanced process control, artificial intelligence and machine learningessential element to this transformation is the exploitation of large amounts of historical process dataand large volumes of data generated in real-time by smart sensors widely used in industry.Exploitation of the information contained in these data requires the use of advanced machine learning

Keywords： big data machine learning artificial intelligence smart sensor cyber–physical system Industry 4.0