Cargando…
Comparison of Artificial Neural Networks and Logistic Regression for 30-days Survival Prediction of Cancer Patients
INTRODUCTION: A machine learning technique that imitates neural system and brain can provide better than traditional methods like logistic regression for survival prediction and create an algorithm by determining influential factors. AIM: To determine the influential factors on survival time of pall...
Autores principales: | Arkin, Funda Secik, Aras, Gulfidan, Dogu, Elif |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Academy of Medical sciences
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382770/ https://www.ncbi.nlm.nih.gov/pubmed/32742062 http://dx.doi.org/10.5455/aim.2020.28.108-113 |
Ejemplares similares
-
Neural networks versus Logistic regression for 30 days all-cause readmission prediction
por: Allam, Ahmed, et al.
Publicado: (2019) -
Artificial Neural Networks Versus Multiple Logistic Regression to Predict 30-Day Mortality After Operations For Type A Ascending Aortic Dissection
por: Macrina, Francesco, et al.
Publicado: (2009) -
Predicting technique survival in peritoneal dialysis patients: comparing artificial neural networks and logistic regression
por: Tangri, Navdeep, et al.
Publicado: (2008) -
Development, Validation and Comparison of Artificial Neural Network Models and Logistic Regression Models Predicting Survival of Unresectable Pancreatic Cancer
por: Tong, Zhou, et al.
Publicado: (2020) -
A Comparison of Logistic Regression Model and Artificial Neural Networks in Predicting of Student’s Academic Failure
por: Teshnizi, Saeed Hosseini, et al.
Publicado: (2015)