stdClass Object
(
    [id] => 5079
    [paper_index] => 202105-02-007153
    [title] => 5G SMART DIABETES: TOWARDS PERSONALIZED DIABETES DIAGNOSIS WITH HEALTHCARE BIG DATA CLOUDS
    [description] => 
    [author] => Sara khulaidi, Syed Muqeet Ur Rahman Asim, Mohd Safi Uddin
    [googlescholar] => https://scholar.google.co.in/scholar?scisbd=2&q=eprajournals.com&hl=en&as_sdt=0,5
    [doi] => 
    [year] => 2021
    [month] => May
    [volume] => 6
    [issue] => 5
    [file] => 1225am_88.EPRA JOURNALS-7153.pdf
    [abstract] => Due to of the profound established and intentional damage suffered by polygenic disorder patients, it’s essential to structure cheap methodologies for the peace of mind and treatment of polygenic disorder. In perspective on our expansive assessment, this text bunches those procedures into polygenic disorder one.0 and polygenic disorder two.0, that show insufficiencies regarding frameworks organization and data. We’ll most likely structure a wise, monetarily perceptive, and sharp polygenic disorder assurance game arrange with redid treatment on these lines. During this article, we tend to initially propose the 5G sensible polygenic disorder system, which mixes the line headways, for example, wearable 2.0, AI, and tremendous information to form sweeping recognizing and examination for patients encountering polygenic disorder. 
    [keywords] => Big Data, cloud storage
    [doj] => 2021-05-30
    [hit] => 2767
    [status] => y
    [award_status] => P
    [orderr] => 88
    [journal_id] => 2
    [googlesearch_link] => 
    [edit_on] => 
    [is_status] => 1
    [journalname] => EPRA International Journal of Research & Development (IJRD)
    [short_code] => IJSR
    [eissn] =>  2455-7838 (Online)
    [pissn] => - -
    [home_page_wrapper] => images/products_image/2-n.png
)
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