Cargando…
Hyperparameter Optimization for COVID-19 Pneumonia Diagnosis Based on Chest CT
Convolutional Neural Networks (CNNs) have been successfully applied in the medical diagnosis of different types of diseases. However, selecting the architecture and the best set of hyperparameters among the possible combinations can be a significant challenge. The purpose of this work is to investig...
Autores principales: | Lacerda, Paulo, Barros, Bruno, Albuquerque, Célio, Conci, Aura |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8003645/ https://www.ncbi.nlm.nih.gov/pubmed/33804609 http://dx.doi.org/10.3390/s21062174 |
Ejemplares similares
-
Pulmonary COVID-19: Learning Spatiotemporal Features Combining CNN and LSTM Networks for Lung Ultrasound Video Classification
por: Barros, Bruno, et al.
Publicado: (2021) -
Automatic COVID-19 and Common-Acquired Pneumonia Diagnosis Using Chest CT Scans
por: Motta, Pedro Crosara, et al.
Publicado: (2023) -
Early Diagnosis of COVID-19 Images Using Optimal CNN Hyperparameters
por: Saad, Mohamed H., et al.
Publicado: (2022) -
Optimal hyperparameter selection of deep learning models for COVID-19 chest X-ray classification
por: Adedigba, Adeyinka P., et al.
Publicado: (2021) -
Chest CT in the emergency department for suspected COVID-19 pneumonia
por: Palmisano, Anna, et al.
Publicado: (2020)