Cargando…
Breast Cancer Detection Using Convoluted Features and Ensemble Machine Learning Algorithm
SIMPLE SUMMARY: This paper presents a breast cancer detection approach where the convoluted features from a convolutional neural network are utilized to train a machine learning model. Results demonstrate that use of convoluted features yields better results than the original features to classify ma...
Autores principales: | Umer, Muhammad, Naveed, Mahum, Alrowais, Fadwa, Ishaq, Abid, Hejaili, Abdullah Al, Alsubai, Shtwai, Eshmawi, Ala’ Abdulmajid, Mohamed, Abdullah, Ashraf, Imran |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737339/ https://www.ncbi.nlm.nih.gov/pubmed/36497497 http://dx.doi.org/10.3390/cancers14236015 |
Ejemplares similares
-
Role of convolutional features and machine learning for predicting student academic performance from MOODLE data
por: Abuzinadah, Nihal, et al.
Publicado: (2023) -
Improving Prediction of Cervical Cancer Using KNN Imputed SMOTE Features and Multi-Model Ensemble Learning Approach
por: Karamti, Hanen, et al.
Publicado: (2023) -
IoT based smart home automation using blockchain and deep learning models
por: Umer, Muhammad, et al.
Publicado: (2023) -
ETCNN: Extra Tree and Convolutional Neural Network-based Ensemble Model for COVID-19 Tweets Sentiment Classification
por: Umer, Muhammad, et al.
Publicado: (2022) -
An Intelligent Framework for Cyber–Physical Satellite System and IoT-Aided Aerial Vehicle Security Threat Detection
por: Alturki, Nazik, et al.
Publicado: (2023)