Predicting survival in veterans with follicular lymphoma using structured electronic health record information and machine learning

Chunyang Li; Vikas Patil; Kelli M. Rasmussen; Christina Yong; Hsu Chih Chien; Debbie Morreall; Jeffrey Humpherys; Brian C. Sauer; Zachary Burningham; Ahmad S. Halwani

doi:10.3390/ijerph18052679

Predicting survival in veterans with follicular lymphoma using structured electronic health record information and machine learning

Chunyang Li
, Vikas Patil
, Kelli M. Rasmussen
, Christina Yong
, Hsu Chih Chien
, Debbie Morreall
, Jeffrey Humpherys
, Brian C. Sauer
, Zachary Burningham
, Ahmad S. Halwani

University of Utah
VA Medical Center

Research output: Contribution to journal › Article › peer-review

Original language	English
Article number	2679
Pages (from-to)	1-19
Number of pages	19
Journal	International Journal of Environmental Research and Public Health
Volume	18
Issue number	5
DOIs	https://doi.org/10.3390/ijerph18052679
State	Published - Mar 1 2021
Externally published	Yes

ASJC Scopus Subject Areas

Pollution
Public Health, Environmental and Occupational Health
Health, Toxicology and Mutagenesis

Keywords

Electronic health records
Follicular lymphoma
Healthcare
Machine learning
Medical and health data
Predictive analytics
Prognosis
Random survival forest
Survival analysis
Veterans health administration

Access to Document

10.3390/ijerph18052679

Cite this

Li, C., Patil, V., Rasmussen, K. M., Yong, C., Chien, H. C., Morreall, D., Humpherys, J., Sauer, B. C., Burningham, Z., & Halwani, A. S. (2021). Predicting survival in veterans with follicular lymphoma using structured electronic health record information and machine learning. International Journal of Environmental Research and Public Health, 18(5), 1-19. Article 2679. https://doi.org/10.3390/ijerph18052679

Predicting survival in veterans with follicular lymphoma using structured electronic health record information and machine learning. / Li, Chunyang; Patil, Vikas; Rasmussen, Kelli M. et al.
In: International Journal of Environmental Research and Public Health, Vol. 18, No. 5, 2679, 01.03.2021, p. 1-19.

Research output: Contribution to journal › Article › peer-review

Li, C, Patil, V, Rasmussen, KM, Yong, C, Chien, HC, Morreall, D, Humpherys, J, Sauer, BC, Burningham, Z & Halwani, AS 2021, 'Predicting survival in veterans with follicular lymphoma using structured electronic health record information and machine learning', International Journal of Environmental Research and Public Health, vol. 18, no. 5, 2679, pp. 1-19. https://doi.org/10.3390/ijerph18052679

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keywords = "Electronic health records, Follicular lymphoma, Healthcare, Machine learning, Medical and health data, Predictive analytics, Prognosis, Random survival forest, Survival analysis, Veterans health administration",

author = "Chunyang Li and Vikas Patil and Rasmussen, \{Kelli M.\} and Christina Yong and Chien, \{Hsu Chih\} and Debbie Morreall and Jeffrey Humpherys and Sauer, \{Brian C.\} and Zachary Burningham and Halwani, \{Ahmad S.\}",

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AU - Morreall, Debbie

AU - Humpherys, Jeffrey

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AU - Halwani, Ahmad S.

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Predicting survival in veterans with follicular lymphoma using structured electronic health record information and machine learning

ASJC Scopus Subject Areas

Keywords

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