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Management of medical and health big data based on integrated learning-based health care system: A review and comparative analysis.
Ye, Yuguang; Shi, Jianshe; Zhu, Daxin; Su, Lianta; Huang, Jianlong; Huang, Yifeng.
Afiliação
  • Ye Y; Faculty of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou 362000, China; Fujian Provincial Key Laboratory of Data Intensive Computing, Quanzhou 362000, China; Key Laboratory of Intelligent Computing and Information Processing, Fujian Province University, Quanzhou 362000, Chin
  • Shi J; Department of General Surgery, Huaqiao University Affiliated Strait Hospital, Quanzhou, Fujian 362000, China.
  • Zhu D; Faculty of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou 362000, China; Fujian Provincial Key Laboratory of Data Intensive Computing, Quanzhou 362000, China; Key Laboratory of Intelligent Computing and Information Processing, Fujian Province University, Quanzhou 362000, Chin
  • Su L; Faculty of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou 362000, China; Key Laboratory of Intelligent Computing and Information Processing, Fujian Province University, Quanzhou 362000, China.
  • Huang J; Faculty of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou 362000, China; Fujian Provincial Key Laboratory of Data Intensive Computing, Quanzhou 362000, China; Key Laboratory of Intelligent Computing and Information Processing, Fujian Province University, Quanzhou 362000, Chin
  • Huang Y; Department of Diagnostic Radiology, Huaqiao University Affiliated Strait Hospital, Quanzhou, Fujian 362000, China. Electronic address: di180ywc@163.com.
Comput Methods Programs Biomed ; 209: 106293, 2021 Sep.
Article em En | MEDLINE | ID: mdl-34364183
ABSTRACT

PURPOSE:

We present a Health Care System (HCS) based on integrated learning to achieve high-efficiency and high-precision integration of medical and health big data, and compared it with an internet-based integrated system.

METHOD:

The method proposed in this paper adopts the Bagging integrated learning method and the Extreme Learning Machine (ELM) prediction model to obtain a high-precision strong learning model. In order to verify the integration efficiency of the system, we compare it with the Internet-based health big data integration system in terms of integration volume, integration efficiency, and storage space capacity.

RESULTS:

The HCS based on integrated learning relies on the Internet in terms of integration volume, integration efficiency, and storage space capacity. The amount of integration is proportional to the time and the integration time is between 170-450 ms, which is only half of the comparison system; whereby the storage space capacity reaches 8.3×28TB.

CONCLUSION:

The experimental results show that the integrated learning-based HCS integrates medical and health big data with high integration volume and integration efficiency, and has high space storage capacity and concurrent data processing performance.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Big Data / Sistema de Aprendizagem em Saúde Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Big Data / Sistema de Aprendizagem em Saúde Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article