Emulating complex simulations by machine learning methods
Abstract Background The aim of the present paper is to construct an emulator of a complex biological system simulator using a machine learning approach. More specifically, the simulator is a patient-specific model that integrates metabolic, nutritional, and lifestyle data to predict the metabolic an...
Guardado en:
Autores principales: | Paola Stolfi, Filippo Castiglione |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
BMC
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/a6a5641db45c41bfb580a4adbb2f8c7d |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
A simulation-based evaluation of machine learning models for clinical decision support: application and analysis using hospital readmission
por: Velibor V. Mišić, et al.
Publicado: (2021) -
Selected abstracts from the 2021 simulation summit
Publicado: (2021) -
Second opinion needed: communicating uncertainty in medical machine learning
por: Benjamin Kompa, et al.
Publicado: (2021) -
Machine intelligence in healthcare—perspectives on trustworthiness, explainability, usability, and transparency
por: Christine M. Cutillo, et al.
Publicado: (2020) -
Beyond performance metrics: modeling outcomes and cost for clinical machine learning
por: James A. Diao, et al.
Publicado: (2021)