Early Prediction of Cognitive Deficit in Very Preterm Infants Using Brain Structural Connectome With Transfer Learning Enhanced Deep Convolutional Neural Networks

Early Prediction of Cognitive Deficit in Very Preterm Infants Using Brain Structural Connectome With Transfer Learning Enhanced Deep Convolutional Neural Networks

Up to 40% of very preterm infants (≤32 weeks’ gestational age) were identified with a cognitive deficit at 2 years of age. Yet, accurate clinical diagnosis of cognitive deficit cannot be made until early childhood around 3–5 years of age. Recently, brain structural connectome that was constructed by...

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Bibliographic Details
Main Authors: Ming Chen, Hailong Li, Jinghua Wang, Weihong Yuan, Mekbib Altaye, Nehal A. Parikh, Lili He
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-09-01
Series:Frontiers in Neuroscience
Subjects:
convolutional neural network
deep learning
cognitive deficit
transfer learning
structural connectome
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2020.00858/full

Internet

https://www.frontiersin.org/article/10.3389/fnins.2020.00858/full

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