Literature DB >> 24743079

Supporting diagnosis and treatment in medical care based on Big Data processing.

Oana-Sorina Lupşe1, Mihaela Crişan-Vida1, Lăcrămioara Stoicu-Tivadar1, Elena Bernard2.   

Abstract

With information and data in all domains growing every day, it is difficult to manage and extract useful knowledge for specific situations. This paper presents an integrated system architecture to support the activity in the Ob-Gin departments with further developments in using new technology to manage Big Data processing - using Google BigQuery - in the medical domain. The data collected and processed with Google BigQuery results from different sources: two Obstetrics & Gynaecology Departments, the TreatSuggest application - an application for suggesting treatments, and a home foetal surveillance system. Data is uploaded in Google BigQuery from Bega Hospital Timişoara, Romania. The analysed data is useful for the medical staff, researchers and statisticians from public health domain. The current work describes the technological architecture and its processing possibilities that in the future will be proved based on quality criteria to lead to a better decision process in diagnosis and public health.

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Year:  2014        PMID: 24743079

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  2 in total

Review 1.  Toward a Literature-Driven Definition of Big Data in Healthcare.

Authors:  Emilie Baro; Samuel Degoul; Régis Beuscart; Emmanuel Chazard
Journal:  Biomed Res Int       Date:  2015-06-02       Impact factor: 3.411

2.  Diabetes classification model based on boosting algorithms.

Authors:  Peihua Chen; Chuandi Pan
Journal:  BMC Bioinformatics       Date:  2018-03-27       Impact factor: 3.169

  2 in total

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