Towards a predictive analytics-based intelligent malaria outbreakwarning system

Babagana Modu; Nereida Polovina; Yang Lan; Savas Konur; A. Taufiq Asyhari; Yonghong Peng

doi:10.3390/app7080836

Towards a predictive analytics-based intelligent malaria outbreakwarning system

Babagana Modu^*, Nereida Polovina, Yang Lan, Savas Konur, A. Taufiq Asyhari, Yonghong Peng

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

42 Citations (SciVal)

Original language	English
Article number	836
Journal	Applied Sciences (Switzerland)
Volume	7
Issue number	8
DOIs	https://doi.org/10.3390/app7080836
Publication status	Published (VoR) - 17 Aug 2017

Funding

Acknowledgments: The authors would like to thank National Centre for Environmental Prediction (NCEP), for their support in providing this work with relevant meteorological data. The author B.M. would like to thank Tertiary Education Trust Fund (tetFund), Nigeria for sponsoring his Ph.D. programme at the University of Bradford, UK. Y.L and S.K. acknowledge Innovate UK KTP010551 grant.

Keywords

Climatic factors
Machine learning
Malaria
Mobile application
Partial least squares model
Prediction
Structural equation modelling

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10.3390/app7080836

Cite this

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author = "Babagana Modu and Nereida Polovina and Yang Lan and Savas Konur and \{Taufiq Asyhari\}, A. and Yonghong Peng",

note = "Funding Information: Acknowledgments: The authors would like to thank National Centre for Environmental Prediction (NCEP), for their support in providing this work with relevant meteorological data. The author B.M. would like to thank Tertiary Education Trust Fund (tetFund), Nigeria for sponsoring his Ph.D. programme at the University of Bradford, UK. Y.L and S.K. acknowledge Innovate UK KTP010551 grant. Publisher Copyright: {\textcopyright} 2017 by the authors.",

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AU - Lan, Yang

AU - Konur, Savas

AU - Taufiq Asyhari, A.

AU - Peng, Yonghong

N1 - Funding Information: Acknowledgments: The authors would like to thank National Centre for Environmental Prediction (NCEP), for their support in providing this work with relevant meteorological data. The author B.M. would like to thank Tertiary Education Trust Fund (tetFund), Nigeria for sponsoring his Ph.D. programme at the University of Bradford, UK. Y.L and S.K. acknowledge Innovate UK KTP010551 grant. Publisher Copyright: © 2017 by the authors.

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KW - Machine learning

KW - Malaria

KW - Mobile application

KW - Partial least squares model

KW - Prediction

KW - Structural equation modelling

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Towards a predictive analytics-based intelligent malaria outbreakwarning system

Funding

Keywords

Access to Document

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