Predicting the Cerebral Blood Flow Change Condition during Brain Strokes using Feature Fusion of FMRI Images and Clinical Features-Reference-Cited by-同舟云学术

Predicting the Cerebral Blood Flow Change Condition during Brain Strokes using Feature Fusion of FMRI Images and Clinical Features

Published:2023-07-06 Issue: Volume: Page:
ISSN:
Container-title:2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
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Author:

Sharma Vandana¹,Sinha Anurag²,Wiryaseputra Michael³,Kumar Biresh⁴,Kumar Tarun Raj⁵,Alkhayyat Ahmed⁶

Affiliation:

1. Christ University, Delhi Campus,Institute of Information Technology,India

2. IGNOU,Department of Computer Science and Information Technology,New Delhi,India

3. Soegijapranata Catholic University,Semarang,Indonesia

4. Amity Univeristy,Department of Computer Science,Jharkhand,India

5. IIT Madras,Computational Mathematics & Data Science,India

6. The Islamic University,College of Technical Engineering,Najaf,Iraq

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10306338/10306339/10306356.pdf?arnumber=10306356

Reference22 articles.

1. Electroconvulsive therapy-induced neuroimaging alterations measured by cerebral blood flow in adolescents with major depressive disorder

2. Predictive Accuracy of Stroke Risk Prediction Models Across Black and White Race, Sex, and Age Groups

3. Hemodynamic transient and functional connectivity follow structural connectivity and cell type over the brain hierarchy

4. Detecting type 2 diabetes mellitus cognitive impairment using whole-brain functional connectivity

5. Cerebral blood flow characteristics of drug-naïve attention-deficit/hyperactivity disorder with social impairment: Evidence for region–symptom specificity;zhang;Frontiers in Neuroscience,2023