Increasing the Density of Laboratory Measures for Machine Learning Applications

Background. The imputation of missingness is a key step in Electronic Health Records (EHR) mining, as it can significantly affect the conclusions derived from the downstream analysis in translational medicine. The missingness of laboratory values in EHR is not at random, yet imputation techniques te...

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Detalles Bibliográficos
Autores principales: Abedi, Vida, Li, Jiang, Shivakumar, Manu K., Avula, Venkatesh, Chaudhary, Durgesh P., Shellenberger, Matthew J., Khara, Harshit S., Zhang, Yanfei, Lee, Ming Ta Michael, Wolk, Donna M., Yeasin, Mohammed, Hontecillas, Raquel, Bassaganya-Riera, Josep, Zand, Ramin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7795258/
https://www.ncbi.nlm.nih.gov/pubmed/33396741
http://dx.doi.org/10.3390/jcm10010103

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7795258/
https://www.ncbi.nlm.nih.gov/pubmed/33396741
http://dx.doi.org/10.3390/jcm10010103

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