Machine learning models for early dengue severity prediction

Infection by dengue-virus is prevalent and a public health issue in tropical countries worldwide. Also, in developing nations, child populations remain at risk of adverse events following an infection by dengue virus, as the necessary care is not always accessible, or health professionals are withou...

Full description

Autores:

Tipo de recurso:

Fecha de publicación:

2016

Institución:

Universidad Tecnológica de Bolívar

Repositorio:

Repositorio Institucional UTB

Idioma:

eng

OAI Identifier:

oai:repositorio.utb.edu.co:20.500.12585/8998

Acceso en línea:

https://hdl.handle.net/20.500.12585/8998

Palabra clave:

Children
Dengue
Logistic regression
Machine learning
Naive bayes
PICU
Severity
SVM
Artificial intelligence
Health risks
Intensive care units
Learning algorithms
Pediatrics
Viruses
Children
Dengue
Logistic regressions
Naive bayes
PICU
Severity
Learning systems

Rights

restrictedAccess

License

http://creativecommons.org/licenses/by-nc-nd/4.0/