Cargando…
266 Inpatient Quality Indicators Risk-Adjustment Using Interactions Selected by Machine Learning Methods
OBJECTIVES/GOALS: Predictive models for health outcomes often have poor calibration potentially due to interactions that are ignored by standard methods. Using AHRQ models for Inpatient Quality Indicator (IQI) 11 Abdominal Aortic Aneurysm Repair and IQI 09 Pancreatic Resection mortality, we hypothes...
Autores principales: | Ray, Monika, Romano, Patrick S. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9209148/ http://dx.doi.org/10.1017/cts.2022.144 |
Ejemplares similares
-
466 Convolutional Neural Networks and Machine Learning in the Identification of Ultrasonographic Features of Ovarian Morphology
por: Pea, Jeffrey, et al.
Publicado: (2022) -
340 Machine Learning Segmentation of Amyloid Load in Ligamentum Flavum Specimens From Spinal Stenosis Patients
por: Wang, Andy Y., et al.
Publicado: (2022) -
331 A Machine Learning-based Pharmacogenomic Association Study of Major Adverse Cardiovascular Events (MACEs) in Caribbean Hispanic Patients on Clopidogrel
por: Arroyo, Luis A. Rosario, et al.
Publicado: (2022) -
259 Proton pump inhibitor use is not significantly associated with severe COVID-19 related outcomes after extensive covariate adjustment
por: Shah, Shailja C., et al.
Publicado: (2022) -
236 Optimizing Haploidentical Donor Selection for Pediatric Hematopoietic Cell Transplant
por: Liberio, Nicole, et al.
Publicado: (2022)