Learning to Discover Explainable Clinical Features With Minimum Supervision

PURPOSE: To compare supervised transfer learning to semisupervised learning for their ability to learn in-depth knowledge with limited data in the optical coherence tomography (OCT) domain. METHODS: Transfer learning with EfficientNet-B4 and semisupervised learning with SimCLR are used in this work....

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Detalles Bibliográficos
Autores principales: Al Turk, Lutfiah, Georgieva, Darina, Alsawadi, Hassan, Wang, Su, Krause, Paul, Alsawadi, Hend, Alshamrani, Abdulrahman Zaid, Saleh, George M., Tang, Hongying Lilian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8762682/
https://www.ncbi.nlm.nih.gov/pubmed/35015061
http://dx.doi.org/10.1167/tvst.11.1.11

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8762682/
https://www.ncbi.nlm.nih.gov/pubmed/35015061
http://dx.doi.org/10.1167/tvst.11.1.11

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