Name
Title | ||
|---|---|---|
Identifying Resting-state Multi-Frequency Biomarkers via Tree-Guided Group Sparse Learning for Schizophrenia Classification. |
Abstract | ||
|---|---|---|
The fractional amplitude of low-frequency fluctuations (fALFF) has been widely used as potential clinical biomarkers for resting-state functional-magnetic-resonance-imaging-based schizophrenia diagnosis. How-ever, previous studies usually measure the fALFF with specific bands from 0.01 to 0.08 Hz, which cannot fully delineate the complex variations of spontaneous fluctuations in the resting-state ... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/JBHI.2018.2796588 | IEEE Journal of Biomedical and Health Informatics |
Keywords | Field | DocType |
Feature extraction,Frequency measurement,Biomarkers,Brain,Diseases,Biomedical imaging,Magnetic resonance imaging | Pattern recognition,Feature selection,Computer science,Medical imaging,Resting state fMRI,Multikernel,Feature extraction,Artificial intelligence,Random forest,Schizophrenia,Sparse learning | Journal |
Volume | Issue | ISSN |
23 | 1 | 2168-2194 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiashuang Huang | 1 | 7 | 3.18 |
| Qi Zhu | 2 | 147 | 11.68 |
| Xiaoke Hao | 3 | 9 | 3.18 |
| Xiaomeng Shi | 4 | 1 | 0.35 |
| Shuzhan Gao | 5 | 1 | 0.35 |
| Xijia Xu | 6 | 3 | 1.06 |
| Daoqiang Zhang | 7 | 2862 | 165.29 |