Prediction of the Risk of Adverse Clinical Outcomes with Machine Learning Techniques in Patients with Noncommunicable Diseases

ABSTRACT: Decision-making in chronic diseases guided by clinical decision support systems that use models including multiple variables based on artificial intelligence requires scientific validation in different populations to optimize the use of limited human, financial, and clinical resources in healt...

Full description

Autores:

Hernández Arango, Alejandro
Arias, María Isabel
Pérez, Viviana
Chavarría, Luis Daniel
Jaimes Barragán, Fabián Alberto

Tipo de recurso:

Article of investigation

Fecha de publicación:

2025

Institución:

Universidad de Antioquia

Repositorio:

Repositorio UdeA

Idioma:

eng

OAI Identifier:

oai:bibliotecadigital.udea.edu.co:10495/45461

Acceso en línea:

https://hdl.handle.net/10495/45461

Palabra clave:

Sistemas de Apoyo a Decisiones Clínicas - organización & administración
Decision Support Systems, Clinical - organization & administration
Registros Electrónicos de Salud
Electronic Health Records
Servicio de Urgencia en Hospital - estadística & datos numéricos
Emergency Service, Hospital - statistics & numerical data
Hospitalización
Hospitalization
Modelos Logísticos
Logistic Models
Aprendizaje Automático
Machine Learning
Redes Neurales de la Computación
Neural Networks, Computer
Medición de Riesgo - métodos
Risk Assessment - methods
https://id.nlm.nih.gov/mesh/D020000
https://id.nlm.nih.gov/mesh/D057286
https://id.nlm.nih.gov/mesh/D004636
https://id.nlm.nih.gov/mesh/D006760
https://id.nlm.nih.gov/mesh/D016015
https://id.nlm.nih.gov/mesh/D000069550
https://id.nlm.nih.gov/mesh/D016571
https://id.nlm.nih.gov/mesh/D018570

Rights

openAccess

License

https://creativecommons.org/licenses/by/4.0/