Retracted: Enhancing Health Risk Prediction with Deep Learning on Big Data and Revised Fusion Node Paradigm

Scientific Programming, Apr 2019

Scientific Programming

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Retracted: Enhancing Health Risk Prediction with Deep Learning on Big Data and Revised Fusion Node Paradigm

Retracted: Enhancing Health Risk Prediction with Deep Learning on Big Data and Revised Fusion Node Paradigm Scientific Programming Received 28 January 2019; Accepted 28 January 2019; Published 8 April 2019 Copyright © 2019 Scientific Programming. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Scientific Programming has retracted the article titled “Enhancing Health Risk Prediction with Deep Learning on Big Data and Revised Fusion Node Paradigm” [1]. The journal understands that the first author was engaged by a subsidiary of AIA Group in China at the time of the study, which was not declared, and AIA Group Limited believe their data may have been used without permission. The authors say no data from AIA were used, but because the information on data collection and the methods may be unclear, they agreed to retraction to avoid any misunderstanding. References H. Zhong and J. Xiao, “Enhancing health risk prediction with deep learning on big data and revised fusion node paradigm,” Scientific Programming, vol. 2017, Article ID 1901876, 18 pages, 2017. View at Publisher · View at Google Scholar · View at Scopus


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Scientific Programming. Retracted: Enhancing Health Risk Prediction with Deep Learning on Big Data and Revised Fusion Node Paradigm, Scientific Programming, 2019, DOI: 10.1155/2019/9757658