Learning Temporal State of Diabetes Patients via Combining Behavioral and Demographic Data-Reference-Cited by-同舟云学术

Learning Temporal State of Diabetes Patients via Combining Behavioral and Demographic Data

Published:2017-08-13 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
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Author:

Xiao Houping¹,Gao Jing²,Vu Long³,Turaga Deepak S.³

Affiliation:

1. SUNY Buffalo & T.J. Watson Research Center, Buffalo, NY, USA

2. SUNY Buffalo, Buffalo, NY, USA

3. IBM T.J. Watson Research Center, Yorktown Heights, NY, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3097983.3098100

Reference29 articles.

1. Progression of liver cirrhosis to HCC: an application of hidden Markov model

2. Alain E Biem Jing Gao Deepak S Turaga Long H Vu and Houping Xiao 2015. Unsupervised multisource temporal anomaly detection. (2015). US Patent App. Alain E Biem Jing Gao Deepak S Turaga Long H Vu and Houping Xiao 2015. Unsupervised multisource temporal anomaly detection. (2015). US Patent App.

3. Latent variable analysis of coping, anxiety/depression, and somatic symptoms in adolescents with chronic pain.

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