Research Square
Cluster analysis driven by unsupervised latent feature learning of intensive care unit medications to identify novel pharmaco-phenotypes of critically ill patients
Publication
, Preprint
Sikora, A; Jeong, H; Yu, M; Chen, X; Murray, B; Kamaleswaran, R
2022
Duke Scholars
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Sikora, A., Jeong, H., Yu, M., Chen, X., Murray, B., & Kamaleswaran, R. (2022). Cluster analysis driven by unsupervised latent feature learning of intensive care unit medications to identify novel pharmaco-phenotypes of critically ill patients. Research Square. https://doi.org/10.21203/rs.3.rs-1745568/v1
Sikora, Andrea, Hayoung Jeong, Mengyun Yu, Xianyan Chen, Brian Murray, and Rishikesan Kamaleswaran. “Cluster analysis driven by unsupervised latent feature learning of intensive care unit medications to identify novel pharmaco-phenotypes of critically ill patients.” Research Square, 2022. https://doi.org/10.21203/rs.3.rs-1745568/v1.
Sikora A, Jeong H, Yu M, Chen X, Murray B, Kamaleswaran R. Cluster analysis driven by unsupervised latent feature learning of intensive care unit medications to identify novel pharmaco-phenotypes of critically ill patients. Research Square. 2022.
Sikora, Andrea, et al. “Cluster analysis driven by unsupervised latent feature learning of intensive care unit medications to identify novel pharmaco-phenotypes of critically ill patients.” Research Square, 2022. Epmc, doi:10.21203/rs.3.rs-1745568/v1.
Sikora A, Jeong H, Yu M, Chen X, Murray B, Kamaleswaran R. Cluster analysis driven by unsupervised latent feature learning of intensive care unit medications to identify novel pharmaco-phenotypes of critically ill patients. Research Square. 2022.