DEELE-Rad: exploiting deep radiomics features in deep learning models using COVID-19 chest X-ray images (2025)
- Authors:
- USP affiliated authors: TRAINA JUNIOR, CAETANO - ICMC ; TRAINA, AGMA JUCI MACHADO - ICMC ; COSTA, MÁRCUS VINÍCIUS LOBO - ICMC ; AGUIAR, ERIKSON JÚLIO DE - ICMC ; RODRIGUES, LUCAS SANTIAGO - ICMC
- Unidade: ICMC
- DOI: 10.1007/s13755-024-00330-6
- Subjects: APRENDIZAGEM PROFUNDA; RECONHECIMENTO DE IMAGEM; DIAGNÓSTICO POR COMPUTADOR; DIAGNÓSTICO POR IMAGEM; RADIOGRAFIA; TÓRAX; COVID-19
- Keywords: Deep radiomics; Radiomics; Deepomics; Deep learning; Machine learning; Medical images
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Health Information Science and Systems
- ISSN: 2047-2501
- Volume/Número/Paginação/Ano: v. 13, n. 1, p. 1-15, Dec. 2025
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
COSTA, Márcus Vinícius Lobo et al. DEELE-Rad: exploiting deep radiomics features in deep learning models using COVID-19 chest X-ray images. Health Information Science and Systems, v. 13, n. 1, p. 1-15, 2025Tradução . . Disponível em: https://doi.org/10.1007/s13755-024-00330-6. Acesso em: 31 dez. 2025. -
APA
Costa, M. V. L., Aguiar, E. J. de, Rodrigues, L. S., Traina Junior, C., & Traina, A. J. M. (2025). DEELE-Rad: exploiting deep radiomics features in deep learning models using COVID-19 chest X-ray images. Health Information Science and Systems, 13( 1), 1-15. doi:10.1007/s13755-024-00330-6 -
NLM
Costa MVL, Aguiar EJ de, Rodrigues LS, Traina Junior C, Traina AJM. DEELE-Rad: exploiting deep radiomics features in deep learning models using COVID-19 chest X-ray images [Internet]. Health Information Science and Systems. 2025 ; 13( 1): 1-15.[citado 2025 dez. 31 ] Available from: https://doi.org/10.1007/s13755-024-00330-6 -
Vancouver
Costa MVL, Aguiar EJ de, Rodrigues LS, Traina Junior C, Traina AJM. DEELE-Rad: exploiting deep radiomics features in deep learning models using COVID-19 chest X-ray images [Internet]. Health Information Science and Systems. 2025 ; 13( 1): 1-15.[citado 2025 dez. 31 ] Available from: https://doi.org/10.1007/s13755-024-00330-6 - A deep learning-based radiomics approach for COVID-19 detection from CXR images using ensemble learning model
- Assessing vulnerabilities of deep learning explainability in medical image analysis under adversarial settings
- Security and privacy in machine learning for health systems: strategies and challenges
- RADAR-MIX: how to uncover adversarial attacks in medical image analysis through explainability
- SentinelAdvMedical: toward adversarial attacks detection on medical image classification via Out-Of-Distribution strategies
- Taking advantage of highly-correlated attributes in similarity queries with missing values
- MedTimeSplit: continual dataset partitioning to mimic real-world settings for federated learning on Non-IID medical image data
- Data augmentation for medical image segmentation: a comparative analysis of traditional techniques and synthetic data generation
- Explorando Espaços Métricos Correlacionados em Consultas por Similaridade sobre Bases de Dados Incompletos
- Exploring diversified similarity with Kundaha
Informações sobre o DOI: 10.1007/s13755-024-00330-6 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
3228506.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
