Inferring multimodal latent topics from electronic health records

Inferring multimodal latent topics from electronic health records

© 2020, The Author(s). Electronic health records (EHR) are rich heterogeneous collections of patient health information, whose broad adoption provides clinicians and researchers unprecedented opportunities for health informatics, disease-risk prediction, actionable clinical recommendations, and prec...

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Bibliographic Details
Main Authors: Li, Yue, Nair, Pratheeksha, Lu, Xing Han, Wen, Zhi, Wang, Yuening, Dehaghi, Amir Ardalan Kalantari, Miao, Yan, Liu, Weiqi, Ordog, Tamas, Biernacka, Joanna M, Ryu, Euijung, Olson, Janet E, Frye, Mark A, Liu, Aihua, Guo, Liming, Marelli, Ariane, Ahuja, Yuri, Davila-Velderrain, Jose, Kellis, Manolis
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:English
Published: Springer Science and Business Media LLC 2021
Online Access:https://hdl.handle.net/1721.1/136021

Internet

https://hdl.handle.net/1721.1/136021

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