A Machine Learning Model for Predicting Intensive Care Unit Admission in Inpatients with COVID-19 Using Clinical Data and Laboratory Biomarkers
<b>Background</b>: Artificial intelligence tools can help improve the clinical management of patients with severe COVID-19. The aim of this study was to validate a machine learning model to predict admission to the Intensive Care Unit (ICU) in individuals with COVID-19. <b>Methods&...
Saved in:
| Main Authors: | Alfonso Heriberto Hernández-Monsalves, Pablo Letelier, Camilo Morales, Eduardo Rojas, Mauricio Alejandro Saez, Nicolás Coña, Javiera Díaz, Andrés San Martín, Paola Garcés, Jesús Espinal-Enriquez, Neftalí Guzmán |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Biomedicines |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-9059/13/5/1025 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Care Team Attributes Predict Likelihood of Utilizing Pharmacogenomic Information During Inpatient Prescribing
by: Zhong Huang, et al.
Published: (2025-04-01) -
FROM PERSONALIZED TO PRECISION MEDICINE
by: K. V. Raskina, et al.
Published: (2017-03-01) -
MALNUTRITION AT HOSPITAL ADMISSION AND ITS ASSOCIATED FACTORS IN INTERNAL MEDICINE INPATIENTS
by: Wita Rizki Amelia, et al.
Published: (2023-06-01) -
Prospects for the Management of Sepsis in an Era of Personalised Medicine
by: Jonathan Cohen
Published: (2019-06-01) -
Organoid‐Guided Precision Medicine: From Bench to Bedside
by: Boqiang Tao, et al.
Published: (2025-05-01)