Predicting the severity of motor neuron disease progression using electronic health record data with a cloud computing Big Data approach.

Authors

Kyung Dae Ko
Tarek El-Ghazawi
Dongkyu Kim
Hiroki Morizono, George Washington University
Pooled Resource Open-Access ALS Clinical Trials Consortium

Document Type

Journal Article

Publication Date

5-2014

Journal

IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Proceedings

Comments

PMCID: PMC4285703 [Available on 2015/5/1]

APA Citation

Ko, K., El-Ghazawi, T., Kim, D., Morizono, H., & Pooled Resource Open-Access ALS Clinical Trials Consortium (2014). Predicting the severity of motor neuron disease progression using electronic health record data with a cloud computing Big Data approach.. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Proceedings, (). Retrieved from https://hsrc.himmelfarb.gwu.edu/smhs_intsysbio_facpubs/111

Peer Reviewed

1