Publisher
Springer Science and Business Media LLC
Subject
Health Information Management,Health Informatics,Information Systems,Medicine (miscellaneous)
Reference5 articles.
1. Choi, J., Dekkers, O. M., and le Cessie, S., A comparison of different methods to handle missing data in the context of propensity score analysis. Eur J Epidemiol. 34(1):23–36, 2019 Jan.
https://doi.org/10.1007/s10654-018-0447-z
Epub 2018 Oct 19.
2. Kartoun, U., Corey, K. E., Simon, T. G., Zheng, H., Aggarwal, R., Ng, K., and Shaw, S. Y., The MELD-Plus: A generalizable prediction risk score in cirrhosis. PLOS ONE 12(10):e0186301, 2017.
3. Mehta, N., Singh, T., Lopez, R., and Alkhouri, N., The heart age is increased in patients with nonalcoholic fatty liver disease and correlates with fibrosis and hepatocyte ballooning. Am J Gastroenterol 111(12):1853–1854, 2016.
4. Waljee, A. K., Mukherjee, A., Singal, A. G., Zhang, Y., Warren, J., Balis, U., Marrero, J., Zhu, J., and Higgins, P. D., Comparison of imputation methods for missing laboratory data in medicine. BMJ Open 3(8), 2013.
5. Beaulieu-Jones, B. K., and Moore, J. H., Missing data imputation in the electronic health record using deeply learned autoencoders. Pac Symp Biocomput 22:207–218, 2017.