2019
DOI: 10.1109/access.2019.2927491
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In Search of Big Medical Data Integration Solutions - A Comprehensive Survey

Abstract: In recent years, the radical advancement of technologies has given rise to an abundance of software applications, social media, and smart devices such as smartphone, sensors, and so on. More extensive use of these applications and tools in various industrial domains has led to data deluge, which has fostered enormous challenges and opportunities. However, it is not only the volume of the data but also the speed, variety, and uncertainty, which are promoting a massive challenge for traditional technologies such… Show more

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Cited by 51 publications
(25 citation statements)
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“…These risk factors lead to natural disaster, social vulnerability and flooding. Shayne et al have carried out a comprehensive study of integration solutions for big medical data [33]. This study has covered the applications, tools and technologies of BDI in the healthcare domain.…”
Section: Review Of Healthcare Sectormentioning
confidence: 99%
“…These risk factors lead to natural disaster, social vulnerability and flooding. Shayne et al have carried out a comprehensive study of integration solutions for big medical data [33]. This study has covered the applications, tools and technologies of BDI in the healthcare domain.…”
Section: Review Of Healthcare Sectormentioning
confidence: 99%
“…A big medical data integration solution is surveyed in [7], which studies different data integration technologies, tools and applications with respect to healthcare domain. Future research ideas with respect to big healthcare data are also presented.…”
Section: Review Of Literaturementioning
confidence: 99%
“…Here, ℎ appears normal to the hyperplane, b is the bias, is the slack variable, = 1,2, … are training samples and is the count of classes. The final decision is made by the equation (7). = ( ( ) + ) (7) In this case, all the classifiers deal with every single pair of class.…”
Section: Disease Prediction By Svm Classifiermentioning
confidence: 99%
“…In the financial industry, the BDA mainly aims to ensure the timeliness and value of financial services. This calls for more in-depth research into data analysis models and relevant algorithms [21][22][23][24][25]. This paper discusses the application mechanism of big data technology in the financial field, gives methods and strategies for preprocessing financial data, builds user portraits based on financial big data, and proposes an MLbased financial BDA model.…”
Section: Introductionmentioning
confidence: 99%