Autoregressive modelling of chromatographic signals from urine samples for prostate cancer diagnosis
This article evaluates autoregressive modeling as a feature extraction method in a database of chromatographic signals from urine samples for non-invasive diagnostic support of prostate cancer in response to the research question: Can chromatographic signals from urine be characterized and used as a...
- Autores:
-
Medina Delgado, Byron
Soto Vergel, Angelo Joseph
PALACIOS ALVARADO, WLAMYR
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2021
- Institución:
- Universidad Francisco de Paula Santander
- Repositorio:
- Repositorio Digital UFPS
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.ufps.edu.co:ufps/781
- Acceso en línea:
- http://repositorio.ufps.edu.co/handle/ufps/781
https://doi.org/10.1088/1742-6596/1938/1/012011
- Palabra clave:
- Rights
- openAccess
- License
- Atribución 4.0 Internacional (CC BY 4.0)