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...
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 |
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Other Authors: | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
Format: | Article |
Language: | English |
Published: |
Springer Science and Business Media LLC
2021
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Online Access: | https://hdl.handle.net/1721.1/136021 |
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