Review paper
Machine Learning Models on ADC Features to Assess Brain Changes of Children With Pierre Robin Sequence
Abstract
In order to evaluate brain changes in young children with Pierre Robin sequence (PRs) using machine learning based on apparent diffusion coefficient (ADC) features, we retrospectively enrolled a total of 60 cases (42 in the training dataset and 18 in the testing dataset) which included 30 PRs and 30 controls from the Children's Hospital Affiliated to the Nanjing Medical University from January 2017–December 2019. There were 21 and nine PRs cases...
Paper Details
Title
Machine Learning Models on ADC Features to Assess Brain Changes of Children With Pierre Robin Sequence
Published Date
Mar 4, 2021
Journal
Volume
12
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