Journal ArticleDOI
Artificial Intelligence for infectious disease Big Data Analytics
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TLDR
It is foreseeable that together with reliable data management platforms AI methods will enable analysis of massive infectious disease and surveillance data effectively to support government agencies, healthcare service providers, and medical professionals to response to disease in the future.Abstract:
Background Since the beginning of the 21st century, the amount of data obtained from public health surveillance has increased dramatically due to the advancement of information and communications technology and the data collection systems now in place. Methods This paper aims to highlight the opportunities gained through the use of Artificial Intelligence (AI) methods to enable reliable disease-oriented monitoring and projection in this information age. Results and Conclusion It is foreseeable that together with reliable data management platforms AI methods will enable analysis of massive infectious disease and surveillance data effectively to support government agencies, healthcare service providers, and medical professionals to response to disease in the future.read more
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How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic.
Nicola Luigi Bragazzi,Haijiang Dai,Giovanni Damiani,Masoud Behzadifar,Mariano Martini,Jianhong Wu +5 more
TL;DR: The present review is aimed at overviewing the potential applications of AI and Big Data in the global effort to manage the pandemic.
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Modeling the Spread of COVID-19 Infection Using a Multilayer Perceptron.
TL;DR: This dataset, intended to be a time-series dataset, is transformed into a regression dataset and used in training a multilayer perceptron (MLP) artificial neural network (ANN) to achieve a worldwide model of the maximal number of patients across all locations in each time unit.
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A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability
Saad M. Khan,Xiaoxuan Liu,Siddharth Nath,Edward Korot,Livia Faes,Siegfried K Wagner,Pearse A. Keane,Neil J. Sebire,Matthew J. Burton,Alastair K Denniston +9 more
TL;DR: Greater visibility is provided for ophthalmological datasets that are publicly available as powerful resources for research and an increasing divide in the representation of different population and disease groups in health data repositories is exposed.
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Artificial Intelligence (AI) Provided Early Detection of the Coronavirus (COVID-19) in China and Will Influence Future Urban Health Policy Internationally
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Exponential Disruptive Technologies and the Required Skills of Industry 4.0
Ocident Bongomin,Gilbert Gilibrays Ocen,Eric Oyondi Nganyi,Alex Musinguzi,Alex Musinguzi,Timothy Omara +5 more
TL;DR: In this paper, a comprehensive literature survey covering the field of engineering, production, and management was done in multidisciplinary databases: Google Scholar, Science Direct, Scopus, Sage, Taylor & Francis, and Emerald Insight.
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