Artificial intelligence in triage of COVID-19 patients
In 2019, COVID-19 began one of the greatest public health challenges in history, reaching pandemic status the following year. Systems capable of predicting individuals at higher risk of progressing to severe forms of the disease could optimize the allocation and direction of resources. In this work,...
Saved in:
| Main Authors: | Yuri Oliveira, Iêda Rios, Paula Araújo, Alinne Macambira, Marcos Guimarães, Lúcia Sales, Marcos Rosa Júnior, André Nicola, Mauro Nakayama, Hermeto Paschoalick, Francisco Nascimento, Carlos Castillo-Salgado, Vania Moraes Ferreira, Hervaldo Carvalho |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2024-12-01
|
| Series: | Frontiers in Artificial Intelligence |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/frai.2024.1495074/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An antibody developability triaging pipeline exploiting protein language models
by: James Sweet-Jones, et al.
Published: (2025-12-01) -
Knowledge Bases and Representation Learning Towards Bug Triaging
by: Qi Wang, et al.
Published: (2025-06-01) -
Predicting early hospital admissions for emergency department patients at the time of triage
by: Shahad M. Al-Ashgar, et al.
Published: (2024-03-01) -
Relationship between In-Hospital Sepsis Prediction Score and Prevalence of Community-Onset Sepsis: Triage for Sepsis Risk Management
by: Kyung Hyun LEE, et al.
Published: (2024-11-01) -
Triage-HF Validation in Heart Failure Clinical Practice: Importance of Episode Duration
by: Daniel García Iglesias, et al.
Published: (2025-06-01)