Cargando…
Data Preprocessing and Augmentation Improved Visual Field Prediction of Recurrent Neural Network with Multi-Central Datasets
INTRODUCTION: The purpose of this study was to determine whether data preprocessing and augmentation could improve visual field (VF) prediction of recurrent neural network (RNN) with multi-central datasets. METHODS: This retrospective study collected data from five glaucoma services between June 200...
Autores principales: | Park, Jeong Rye, Kim, Sangil, Kim, Taehyeong, Jin, Sang Wook, Kim, Jung Lim, Shin, Jonghoon, Lee, Seung Uk, Jang, Geunsoo, Hu, Yuanmeng, Lee, Ji Woong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
S. Karger AG
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10357387/ https://www.ncbi.nlm.nih.gov/pubmed/37231880 http://dx.doi.org/10.1159/000531144 |
Ejemplares similares
-
Visual field prediction using a deep bidirectional gated recurrent unit network model
por: Kim, Hwayeong, et al.
Publicado: (2023) -
Early detection of norovirus outbreak using machine learning methods in South Korea
por: Lee, Sieun, et al.
Publicado: (2022) -
Quality control and preprocessing of metagenomic datasets
por: Schmieder, Robert, et al.
Publicado: (2011) -
Preprocessed Consortium for Neuropsychiatric Phenomics dataset
por: Gorgolewski, Krzysztof J., et al.
Publicado: (2017) -
A visual working memory dataset collection with bootstrap Independent Component Analysis for comparison of electroencephalographic preprocessing pipelines
por: Artoni, Fiorenzo, et al.
Publicado: (2018)