Using data mining techniques to determine whether to outsource medical equipment maintenance tasks in real contexts
The purpose of this study was to determine whether the maintenance of medical equipment should be outsourced (or not). For this, we used data mining techniques called decision trees. We (1) collected 2364 maintenance works orders from 62 medical devices installed in a 900-bed hospital; (2) then we r...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2019
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/24266
- Acceso en línea:
- https://doi.org/10.1007/978-981-10-9023-3_52
https://repository.urosario.edu.co/handle/10336/24266
- Palabra clave:
- Biomedical engineering
Biomedical equipment
Decision trees
Errors
Maintenance
Medical computing
Obsolescence
Outsourcing
Trees (mathematics)
Alternating decision trees
Clinical engineering
Decision stumps
Maintenance management
Maintenance tasks
Maintenance work
Medical Devices
Medical equipment maintenance
Data mining
Clinical engineering
Data mining
Decision tree
Maintenance management
Outsourcing
- Rights
- License
- http://purl.org/coar/access_right/c_abf2