Cargando…
EpistoNet: an ensemble of Epistocracy-optimized mixture of experts for detecting COVID-19 on chest X-ray images
The Coronavirus has spread across the world and infected millions of people, causing devastating damage to the public health and global economies. To mitigate the impact of the coronavirus a reliable, fast, and accurate diagnostic system should be promptly implemented. In this study, we propose Epis...
Autores principales: | Mousavi Mojab, Seyed Ziae, Shams, Seyedmohammad, Fotouhi, Farshad, Soltanian-Zadeh, Hamid |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8566470/ https://www.ncbi.nlm.nih.gov/pubmed/34732741 http://dx.doi.org/10.1038/s41598-021-00524-y |
Ejemplares similares
-
DeBoNet: A deep bone suppression model ensemble to improve disease detection in chest radiographs
por: Rajaraman, Sivaramakrishnan, et al.
Publicado: (2022) -
Ensemble of EfficientNets for the Diagnosis of Tuberculosis
por: Oloko-Oba, Mustapha, et al.
Publicado: (2021) -
Expert .NET Micro Framework
por: Kühner, Jens
Publicado: (2008) -
ET-NET: an ensemble of transfer learning models for prediction of COVID-19 infection through chest CT-scan images
por: Kundu, Rohit, et al.
Publicado: (2021) -
Combining artificial neural nets: ensemble and modular multi-net systems
por: Sharkey, Amanda J C
Publicado: (1999)