Densification of longitudinal emr for improved phenotyping
AssigneeInternational Business Machines Corporation
InventorsJianying Hu, Fei Wang, Jiayu Zhou
Life of this patent
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Abstract
Systems and methods for data densification include representing patient data as a sparse patient matrix for each patient. The sparse patient matrix is decomposed into a plurality of matrices including a concept matrix indicating medical concepts of the patient data and an evolution matrix indicating a temporal relationship of the medical concepts. Missing information in the sparse patient matrix is imputed using a processor based on the plurality of matrices to provide a densified patient matrix.
Claims20
A method for data densification, comprising:
- representing patient data as a sparse patient matrix for each patient;
- decomposing the sparse patient matrix into a plurality of matrices including a concept matrix indicating medical concepts of the patient data and an evolution matrix indicating a temporal relationship of the medical concepts;
- and
- imputing missing information in the sparse patient matrix using a processor based on the plurality of matrices to provide a densified patient matrix.
A computer readable storage medium comprising a computer readable program for data densification, wherein the computer readable program when executed on a computer causes the computer to perform the steps of:
- representing patient data as a sparse patient matrix for each patient;
- decomposing the sparse patient matrix into a plurality of matrices including a concept matrix indicating medical concepts of the patient data and an evolution matrix indicating a temporal relationship of the medical concepts;
- and
- imputing missing information in the sparse patient matrix based on the plurality of matrices to provide a densified patient matrix.
A system for data densification, comprising:
- a matrix formation module configured to represent patient data as a sparse patient matrix for each patient;
- a factorization module configured to decompose the sparse patient matrix into a plurality of matrices including a concept matrix indicating medical concepts of the patient data and an evolution matrix indicating a temporal relationship of the medical concepts;
- and
- an imputation module configured to impute missing information in the sparse patient matrix using a processor based on the plurality of matrices to provide a densified patient matrix.
Dependencies are inferred from the claim text.