scholarly journals Remodeling Pearson's Correlation for Functional Brain Network Estimation and Autism Spectrum Disorder Identification

2017 ◽  
Vol 11 ◽  
Author(s):  
Weikai Li ◽  
Zhengxia Wang ◽  
Limei Zhang ◽  
Lishan Qiao ◽  
Dinggang Shen
2012 ◽  
Vol 50 (14) ◽  
pp. 3653-3662 ◽  
Author(s):  
Pablo Barttfeld ◽  
Bruno Wicker ◽  
Sebastián Cukier ◽  
Silvana Navarta ◽  
Sergio Lew ◽  
...  

2021 ◽  
Vol 14 ◽  
Author(s):  
Jingjing Gao ◽  
Mingren Chen ◽  
Yuanyuan Li ◽  
Yachun Gao ◽  
Yanling Li ◽  
...  

Autism spectrum disorder (ASD) is a range of neurodevelopmental disorders with behavioral and cognitive impairment and brings huge burdens to the patients’ families and the society. To accurately identify patients with ASD from typical controls is important for early detection and early intervention. However, almost all the current existing classification methods for ASD based on structural MRI (sMRI) mainly utilize the independent local morphological features and do not consider the covariance patterns of these features between regions. In this study, by combining the convolutional neural network (CNN) and individual structural covariance network, we proposed a new framework to classify ASD patients with sMRI data from the ABIDE consortium. Moreover, gradient-weighted class activation mapping (Grad-CAM) was applied to characterize the weight of features contributing to the classification. The experimental results showed that our proposed method outperforms the currently used methods for classifying ASD patients with the ABIDE data and achieves a high classification accuracy of 71.8% across different sites. Furthermore, the discriminative features were found to be mainly located in the prefrontal cortex and cerebellum, which may be the early biomarkers for the diagnosis of ASD. Our study demonstrated that CNN is an effective tool to build the framework for the diagnosis of ASD with individual structural covariance brain network.


2016 ◽  
Vol 234 (12) ◽  
pp. 3425-3431 ◽  
Author(s):  
Evie Malaia ◽  
Erik Bates ◽  
Benjamin Seitzman ◽  
Katherine Coppess

2020 ◽  
Vol 35 (4) ◽  
pp. 246-256
Author(s):  
Elizabeth Crais ◽  
Cara S. McComish ◽  
Emily F. Kertcher ◽  
Steve Hooper ◽  
Rebecca Pretzel ◽  
...  

This study explored caregivers’ perspectives on facilitators and barriers to screening, diagnosis, and identifying and accessing other services for young children with autism spectrum disorder (ASD); and caregivers’ suggestions for improving the process. Eight focus groups with 55 caregivers were conducted. Four groups had a mix of White, African American, and Asian caregivers, and to gain broader populations, we recruited two groups of Spanish-speaking and two groups of American Indian caregivers. Some caregivers reported that their child and they received excellent services; however, the majority reported concerns about the services they and their child received. The findings also indicated a lower age of diagnosis and a smaller gap between concerns and diagnosis for White non-Hispanic children compared with Hispanic non-White children. Caregivers had many suggestions for ways to improve the process.


2015 ◽  
Vol 126 (8) ◽  
pp. e91-e92 ◽  
Author(s):  
E. Hoffmann ◽  
C. Brück ◽  
B. Kreifelts ◽  
T. Ethofer ◽  
D. Wildgruber

2019 ◽  
Vol 12 (12) ◽  
pp. 1758-1773 ◽  
Author(s):  
Abigail Dickinson ◽  
Kandice J. Varcin ◽  
Mustafa Sahin ◽  
Charles A. Nelson ◽  
Shafali S. Jeste

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