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[HTML][HTML] Longitudinal K-means approaches to clustering and analyzing EHR opioid use trajectories for clinical subtypes

S Mullin, J Zola, R Lee, J Hu, B MacKenzie… - Journal of biomedical …, 2021 - Elsevier
Identification of patient subtypes from retrospective Electronic Health Record (EHR) data is
fraught with inherent modeling issues, such as missing data and variable length time …
被引用次数：34 相关文章

Longitudinal K-means approaches to clustering and analyzing EHR opioid use trajectories for clinical subtypes.

S Mullin, J Zola, R Lee, J Hu, B MacKenzie… - Journal of Biomedical …, 2021 - europepmc.org
Identification of patient subtypes from retrospective Electronic Health Record (EHR) data is
fraught with inherent modeling issues, such as missing data and variable length time …

Longitudinal K-means approaches to clustering and analyzing EHR opioid use trajectories for clinical subtypes

S Mullin, J Zola, R Lee, J Hu, B MacKenzie, A Brickman… - 2021 - dl.acm.org
Identification of patient subtypes from retrospective Electronic Health Record (EHR) data is
fraught with inherent modeling issues, such as missing data and variable length time …

Longitudinal K-means approaches to clustering and analyzing EHR opioid use trajectories for clinical subtypes

S Mullin, J Zola, R Lee, J Hu… - Journal of …, 2021 - portal.findresearcher.sdu.dk
Identification of patient subtypes from retrospective Electronic Health Record (EHR) data is
fraught with inherent modeling issues, such as missing data and variable length time …
[PDF] nsf.gov

[PDF][PDF] Longitudinal K-means approaches to clustering and analyzing EHR opioid use trajectories for clinical subtypes

S Mullin, J Zola, R Lee, J Hu, B MacKenzie… - Journal of Biomedical …, 2021 - par.nsf.gov
Identification of patient subtypes from retrospective Electronic Health Record (EHR) data is
fraught with inherent modeling issues, such as missing data and variable length time …
[HTML] nih.gov

[HTML][HTML] Longitudinal K-means approaches to clustering and analyzing EHR opioid use trajectories for clinical subtypes

S Mullin, J Zola, R Lee, J Hu, B MacKenzie… - Journal of biomedical …, 2021 - ncbi.nlm.nih.gov
Identification of patient subtypes from retrospective Electronic Health Record (EHR) data is
fraught with inherent modeling issues, such as missing data and variable length time …

Longitudinal K-means approaches to clustering and analyzing EHR opioid use trajectories for clinical subtypes

S Mullin, J Zola, R Lee, J Hu… - Journal of …, 2021 - pubmed.ncbi.nlm.nih.gov
Identification of patient subtypes from retrospective Electronic Health Record (EHR) data is
fraught with inherent modeling issues, such as missing data and variable length time …
[PDF] buffalo.edu

[PDF][PDF] Longitudinal K-means approaches to clustering and analyzing EHR opioid use trajectories for clinical subtypes

S Mullin, J Zola, R Lee, J Hu, B MacKenzie… - Journal of Biomedical …, 2021 - cse.buffalo.edu
Identification of patient subtypes from retrospective Electronic Health Record (EHR) data is
fraught with inherent modeling issues, such as missing data and variable length time …

Longitudinal K-means approaches to clustering and analyzing EHR opioid use trajectories for clinical subtypes

S Mullin, J Zola, R Lee, J Hu… - Journal of …, 2021 - findresearchersdu.elsevierpure.com
Identification of patient subtypes from retrospective Electronic Health Record (EHR) data is
fraught with inherent modeling issues, such as missing data and variable length time …