Abstract：
:The main goal of this article is to identify the main dimensions of a model proposal for increasing the potential of big data research in Healthcare for medical doctors' (MDs') learning, which appears as a major issue in continuous medical education and learning. The paper employs a systematic literature review of main scientific databases (PubMed and Google Scholar), using the VOSviewer software tool, which enables the visualization of scientific landscapes. The analysis includes a co-authorship data analysis as well as the co-occurrence of terms and keywords. The results lead to the construction of the learning model proposed, which includes four health big data key areas for MDs' learning: 1) data transformation is related to the learning that occurs through medical systems; 2) health intelligence includes the learning regarding health innovation based on predictions and forecasting processes; 3) data leveraging regards the learning about patient information; and 4) the learning process is related to clinical decision-making, focused on disease diagnosis and methods to improve treatments. Practical models gathered from the scientific databases can boost the learning process and revolutionise the medical industry, as they store the most recent knowledge and innovative research.
journal_name
J Med Systjournal_title
Journal of medical systemsauthors
Au-Yong-Oliveira M,Pesqueira A,Sousa MJ,Dal Mas F,Soliman Mdoi
10.1007/s10916-020-01691-7subject
Has Abstractpub_date
2021-01-07 00:00:00pages
13issue
1eissn
0148-5598issn
1573-689Xpii
10.1007/s10916-020-01691-7journal_volume
45pub_type
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