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...

ver descrição completa

Detalhes bibliográficos

Principais autores:	Adam Hanif, MD, İlkay Yıldız, PhD, Peng Tian, PhD, Beyza Kalkanlı, BS, Deniz Erdoğmuş, PhD, Stratis Ioannidis, PhD, Jennifer Dy, PhD, Jayashree Kalpathy-Cramer, PhD, Susan Ostmo, MS, Karyn Jonas, BSN, R. V. Paul Chan, MD, MBA, Michael F. Chiang, MD, J. Peter Campbell, MD, MPH
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Elsevier 2022-06-01
Colecção:	Ophthalmology Science
Assuntos:	Artificial intelligence Deep learning Labels Neural networks Retinopathy of prematurity
Acesso em linha:	http://www.sciencedirect.com/science/article/pii/S2666914522000112
Tags:	Adicionar Tag Sem tags, seja o primeiro a adicionar uma tag!