Semi-supervised approach to event time annotation using longitudinal electronic health records

Liang Liang; Jue Hou; Hajime Uno; Kelly Cho; Yanyuan Ma; Tianxi Cai

doi:10.1007/s10985-022-09557-5

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Semi-supervised approach to event time annotation using longitudinal electronic health records

Liang Liang Jue Hou Hajime Uno Kelly Cho Yanyuan Ma Tianxi Cai

Year: 2022 Journal: Lifetime Data Analysis Vol: 28 (3)Pages: 428-491 Publisher: Springer Science+Business Media

DOI: 10.1007/s10985-022-09557-5

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Keywords:

Computer science Event (particle physics) Annotation Estimator Time point Data mining Covariate Artificial intelligence Machine learning Statistics Mathematics

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Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

Machine Learning in Healthcare

Physical Sciences → Computer Science → Artificial Intelligence

Metabolomics and Mass Spectrometry Studies

Life Sciences → Biochemistry, Genetics and Molecular Biology → Molecular Biology

Semi-supervised approach to event time annotation using longitudinal electronic health records

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