Cargando…
A novel deep autoencoder based survival analysis approach for microarray dataset
BACKGROUND: Breast cancer is one of the major causes of mortality globally. Therefore, different Machine Learning (ML) techniques were deployed for computing survival and diagnosis. Survival analysis methods are used to compute survival probability and the most important factors affecting that proba...
Autores principales: | Torkey, Hanaa, Atlam, Mostafa, El-Fishawy, Nawal, Salem, Hanaa |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080419/ https://www.ncbi.nlm.nih.gov/pubmed/33981841 http://dx.doi.org/10.7717/peerj-cs.492 |
Ejemplares similares
-
Coronavirus disease 2019 (COVID-19): survival analysis using deep learning and Cox regression model
por: Atlam, Mostafa, et al.
Publicado: (2021) -
An ensemble-based drug–target interaction prediction approach using multiple feature information with data balancing
por: El-Behery, Heba, et al.
Publicado: (2022) -
Efficient machine learning model for predicting drug-target interactions with case study for Covid-19
por: El-Behery, Heba, et al.
Publicado: (2021) -
RN-Autoencoder: Reduced Noise Autoencoder for classifying imbalanced cancer genomic data
por: Arafa, Ahmed, et al.
Publicado: (2023) -
An Enhanced Multiple Sclerosis Disease Diagnosis via an Ensemble Approach
por: Torkey, Hanaa, et al.
Publicado: (2022)