gEM/GANN: A multivariate computational strategy for auto-characterizing relationships between cellular and clinical phenotypes and predicting disease progression time using high-dimensional flow cytometry data
نویسندگان
چکیده
منابع مشابه
Predicting Disease Progression with a Model for Multivariate Longitudinal Clinical Data
Accurate prediction of the future trajectory of a disease is an important challenge in personalized medicine and population health management. However, many complex chronic diseases exhibit large degrees of heterogeneity, and furthermore there is not always a single readily available biomarker to quantify disease severity. Even when such a clinical variable exists, there are often additional re...
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Flow cytometry is a technique for rapidly quantifying physical and chemical properties of large numbers of cells. In clinical applications, flow cytometry data must be manually “gated” to identify cell populations of interest. While several researchers have investigated statistical methods for automating this process, most of them falls under the framework of unsupervised learning and mixture m...
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ژورنال
عنوان ژورنال: Cytometry Part A
سال: 2015
ISSN: 1552-4922
DOI: 10.1002/cyto.a.22622