Deep learning model calibration for improving performance in class-imbalanced medical image classification tasks

In medical image classification tasks, it is common to find that the number of normal samples far exceeds the number of abnormal samples. In such class-imbalanced situations, reliable training of deep neural networks continues to be a major challenge, therefore biasing the predicted class probabilit...

Descripción completa

Detalles Bibliográficos
Autores principales: Rajaraman, Sivaramakrishnan, Ganesan, Prasanth, Antani, Sameer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8794113/
https://www.ncbi.nlm.nih.gov/pubmed/35085334
http://dx.doi.org/10.1371/journal.pone.0262838

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8794113/
https://www.ncbi.nlm.nih.gov/pubmed/35085334
http://dx.doi.org/10.1371/journal.pone.0262838

Ejemplares similares