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...
- 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/