Time-ordered comorbidity correlations identify patients at risk of mis- and overdiagnosis
Abstract Diagnostic errors are common and can lead to harmful treatments. We present a data-driven, generic approach for identifying patients at risk of being mis- or overdiagnosed, here exemplified by chronic obstructive pulmonary disease (COPD). It has been estimated that 5–60% of all COPD cases a...
Guardado en:
Autores principales: | Isabella Friis Jørgensen, Søren Brunak |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/b6489d947fb34838b989ee7d25794cb5 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Identifying unreliable predictions in clinical risk models
por: Paul D. Myers, et al.
Publicado: (2020) -
Identifying undercompensated groups defined by multiple attributes in risk adjustment
por: Anna Zink, et al.
Publicado: (2021) -
Using digital surveillance tools for near real-time mapping of the risk of infectious disease spread
por: Sangeeta Bhatia, et al.
Publicado: (2021) -
Bioinformatics Analysis for Identifying Pertinent Pathways and Genes in Sepsis
por: Yiran Li, et al.
Publicado: (2021) -
Audit Data Analysis and Application Based on Correlation Analysis Algorithm
por: Jifan Chen, et al.
Publicado: (2021)