A LIME-Based Explainable Machine Learning Model for Predicting the Severity Level of COVID-19 Diagnosed Patients
The fast and seemingly uncontrollable spread of the novel coronavirus disease (COVID-19) poses great challenges to an already overloaded health system worldwide. It thus exemplifies an urgent need for fast and effective triage. Such triage can help in the implementation of the necessary measures to...
Guardado en:
Autores principales: | Freddy Gabbay, Shirly Bar-Lev, Ofer Montano, Noam Hadad |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/85adda00d46d46428fae7e1c91ec9428 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Explainable Artificial Intelligence for Human-Machine Interaction in Brain Tumor Localization
por: Morteza Esmaeili, et al.
Publicado: (2021) -
Turning the blackbox into a glassbox: An explainable machine learning approach for understanding hospitality customer
por: Ritu Sharma, et al.
Publicado: (2021) -
Evidence-Based and Explainable Smart Decision Support for Quality Improvement in Stainless Steel Manufacturing
por: Henna Tiensuu, et al.
Publicado: (2021) -
Using Explainable Machine Learning to Improve Intensive Care Unit Alarm Systems
por: José A. González-Nóvoa, et al.
Publicado: (2021) -
Systematic Literature Review on Machine Learning and Student Performance Prediction: Critical Gaps and Possible Remedies
por: Boran Sekeroglu, et al.
Publicado: (2021)