Cargando…
Using decision tree learning to predict the responsiveness of hepatitis C patients to drug treatment
The recommended treatment for patients with chronic hepatitis C, pegylated interferon α (PEG-IFN-α) plus rebavirin (RBV), does not provide a sustained virologic response in all patients, especially those with hepatitis C virus (HCV) genotype 1. It is therefore important to predict whether or not a n...
Autores principales: | Kawamura, Yoshihiro, Takasaki, Shigeru, Mizokami, Masashi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3645974/ https://www.ncbi.nlm.nih.gov/pubmed/23650587 http://dx.doi.org/10.1016/j.fob.2012.04.007 |
Ejemplares similares
-
Selecting effective siRNA sequences by using radial basis function network and decision tree learning
por: Takasaki, Shigeru, et al.
Publicado: (2006) -
Accurate Prediction of Advanced Liver Fibrosis Using the Decision Tree Learning Algorithm in Chronic Hepatitis C Egyptian Patients
por: Hashem, Somaya, et al.
Publicado: (2016) -
Decision Trees for Predicting the Physiological Responses of Rabbits
por: Ferraz, Patrícia Ferreira Ponciano, et al.
Publicado: (2019) -
Decision trees: from efficient prediction to responsible AI
por: Blockeel, Hendrik, et al.
Publicado: (2023) -
Fall prediction using decision tree analysis in acute care
units
por: Tamura, Shuntaro, et al.
Publicado: (2020)