Cargando…
Improved Training Efficiency for Retinopathy of Prematurity Deep Learning Models Using Comparison versus Class Labels
PURPOSE: To compare the efficacy and efficiency of training neural networks for medical image classification using comparison labels indicating relative disease severity versus diagnostic class labels from a retinopathy of prematurity (ROP) image dataset. DESIGN: Evaluation of diagnostic test or tec...
Autores principales: | Hanif, Adam, Yıldız, İlkay, Tian, Peng, Kalkanlı, Beyza, Erdoğmuş, Deniz, Ioannidis, Stratis, Dy, Jennifer, Kalpathy-Cramer, Jayashree, Ostmo, Susan, Jonas, Karyn, Chan, R. V. Paul, Chiang, Michael F., Campbell, J. Peter |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9560533/ https://www.ncbi.nlm.nih.gov/pubmed/36249702 http://dx.doi.org/10.1016/j.xops.2022.100122 |
Ejemplares similares
-
Plus Disease in Retinopathy of Prematurity: Convolutional Neural Network Performance Using a Combined Neural Network and Feature Extraction Approach
por: Yildiz, Veysi M., et al.
Publicado: (2020) -
Oxygenation Fluctuations Associated with Severe Retinopathy of Prematurity: Insights from a Multimodal Deep Learning Approach
por: Lin, Wei-Chun, et al.
Publicado: (2023) -
Quantification of Early Neonatal Oxygen Exposure as a Risk Factor for Retinopathy of Prematurity Requiring Treatment
por: Chen, Jimmy S., et al.
Publicado: (2021) -
Synthetic Medical Images for Robust, Privacy-Preserving Training of Artificial Intelligence: Application to Retinopathy of Prematurity Diagnosis
por: Coyner, Aaron S., et al.
Publicado: (2022) -
Artificial Intelligence in Retinopathy of Prematurity Diagnosis
por: Scruggs, Brittni A., et al.
Publicado: (2020)