IEEE Access special section editorial: health informatics for the developing world
Editorial
Article Title | IEEE Access special section editorial: health informatics for the developing world |
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ERA Journal ID | 210567 |
Article Category | Editorial |
Authors | Qadir, Junaid (Author), Mujeeb-U-Rahman, Muhammad (Author), Rehmani, Mubashir Husain (Author), Pathan, Al-Sakib Khan (Author), Imran, Muhammad Ali (Author), Hussain, Amir (Author), Rana, Rajib (Author) and Luo, Bin (Author) |
Journal Title | IEEE Access |
Journal Citation | 5, pp. 27818-27823 |
Number of Pages | 6 |
Year | 2017 |
Publisher | IEEE (Institute of Electrical and Electronics Engineers) |
Place of Publication | United States |
ISSN | 2169-3536 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/ACCESS.2017.2783118 |
Web Address (URL) | https://ieeexplore.ieee.org/document/8262687/ |
Abstract | We live in a world with growing disparity in the quality of life available to people in the developed and developing countries. Healthcare in the developing world is fraught with numerous problems such as the lack of health infrastructure, and human resources, which results in very limited health coverage. The field of health informatics has made great strides in recent years towards improving public health systems in the developing world by augmenting them with state-of-the-art information and communication technologies (ICT). Through real-world deployment of these technologies, there is real hope that the health industry in the developing world will progress from its current, largely dysfunctional state to one that is more effective, personalized, and cost effective. Health informatics can usher a new era of personalized health analytics, with the potential to transform healthcare in the developing world. In conjunction with mHealth and eHealth, many other important health informatics trends—such as artificial intelligence (AI), machine learning (ML), big data, crowdsourcing, cloud computing—are also emerging. Exponentially growing heterogeneous data, with the help of big data analytics, has the potential to provide descriptive, predictive, and prescriptive health insights as well as enable new applications such as telemedicine and remote diagnostics and surgery. Such systems could enhance the overall process of monitoring, diagnosis, and prognosis of diseases. |
ANZSRC Field of Research 2020 | 461199. Machine learning not elsewhere classified |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Information Technology University, Pakistan |
Waterford Institute of Technology, Ireland | |
Southeast University, Bangladesh | |
University of Glasgow, United Kingdom | |
University of Stirling, United Kingdom | |
Institute for Resilient Regions | |
Anhui University, China | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q4vxq/ieee-access-special-section-editorial-health-informatics-for-the-developing-world
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