Conference proceeding
Interpatient Similarity-based Imputation of Missing Data in Electronic Health Records
2019 IEEE International Conference on Healthcare Informatics (ICHI)
Jun 2019
Abstract
In the past few years, the development of systems for collecting patient data in the form of electronic health records (EHR) has progressed substantially. However, EHR data is generally heterogeneous, temporal, and incomplete (Hripcsak and Albers 2012). Because most of the analytical methods developed for data-driven prediction and modeling assume that the input data set has no missing data, there have been extensive efforts both in health care community and other fields to find the best methods for missing data pre-processing and imputation.
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Details
- Title
- Interpatient Similarity-based Imputation of Missing Data in Electronic Health Records
- Creators
- Ali Jazayeri - Drexel UniversityOu Stella Liang - Drexel UniversityChristopher C Yang - Drexel University
- Publication Details
- 2019 IEEE International Conference on Healthcare Informatics (ICHI)
- Conference
- 2019 IEEE International Conference on Healthcare Informatics (ICHI)
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Scopus ID
- 2-s2.0-85075935668
- Other Identifier
- 991019173517404721