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...

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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)