| Literature DB >> 31472738 |
Ellen Kim1, Samuel M Rubinstein2, Kevin T Nead3, Andrzej P Wojcieszynski3, Peter E Gabriel3, Jeremy L Warner4.
Abstract
Electronic health records (EHR) have been implemented successfully in a majority of United States healthcare systems in some form. There has been a rise in secondary uses of EHR, especially for research. EHR data is large, heterogenous, incomplete, noisy, and primarily created for purposes other than research. This presents many challenges, many of which are beginning to be overcome with the application of computer science artificial intelligence techniques, such as natural language processing and machine learning. EHR are gradually being redesigned to facilitate future research, though we are still far from a "complete EHR."Mesh：
Year: 2019 PMID： 31472738 DOI： 10.1016/j.semradonc.2019.05.010
Source DB: PubMed Journal: Semin Radiat Oncol ISSN： 1053-4296 Impact factor: 5.934