ISeeU2: Visually interpretable mortality prediction inside the ICU using deep learning and free-text medical notes

Accurate mortality prediction allows Intensive Care Units (ICUs) to adequately benchmark clinical practice and identify patients with unexpected outcomes. Traditionally, simple statistical models have been used to assess patient death risk, many times with sub-optimal performance. On the other hand...

Full description

Autores:
Caicedo-Torres, William
Gutierrez, Jairo
Tipo de recurso:
Fecha de publicación:
2022
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/12197
Acceso en línea:
https://hdl.handle.net/20.500.12585/12197
Palabra clave:
Imbalanced Data;
Cost-Sensitive Learning;
Data Classification
LEMB
Rights
openAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/