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Disease progression subtype discovery from longitudinal EMR data with a majority of missing values and unknown initial time points
Electronic medical records (EMR) contain a longitudinal collection of laboratory data that contains valuable phenotypic information on disease progression of a large collection of patients. These data can be potentially used in medical research or patient care; finding disease progression subtypes i...
Sparad:
| I publikationen: | AMIA Annu Symp Proc |
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| Huvudupphovsmän: | , , , , , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
American Medical Informatics Association
2014
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4419979/ https://ncbi.nlm.nih.gov/pubmed/25954377 |
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