Deep Learning Architectures for Multi-Label Classification of Intelligent Health Risk Prediction

Authors

Andrew Maxwell, University of Southern MississippiFollow
Runzhi Li, Zhengzhou University
Bei Yang, Zhengzhou UniversityFollow
Heng Weng, The Second Affiliated Hospital of Guangzhou University of Chinese MedicineFollow
Aihua Ou, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine
Huixiao Hong, U.S. Food and Drug Administration, National Center for Toxicological ResearchFollow
Zhaoxian Zhou, University of Southern Mississippi
Ping Gong, U.S. Army Engineer Research and Development CenterFollow
Chaoyang Zhang, University of Southern MississippiFollow

Document Type

Article

Publication Date

12-28-2017

School

Computing Sciences and Computer Engineering

Comments

Published by 'BMC Bioinformatics' at 10.1186/s12859-017-1898-z.

Publication Title

BMC Bioinformatics

Volume

18

Issue

S14

First Page

121

Last Page

131

Recommended Citation

Maxwell, A., Li, R., Yang, B., Weng, H., Ou, A., Hong, H., Zhou, Z., Gong, P., Zhang, C. (2017). Deep Learning Architectures for Multi-Label Classification of Intelligent Health Risk Prediction. BMC Bioinformatics, 18(S14), 121-131.
Available at: https://aquila.usm.edu/fac_pubs/16623