New Feature for Schizophrenia Classification Based on Functionally Homogeneous Brain Regions
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-50381-8_50
Reference21 articles.
1. Algumaei, A.H., Algunaid, R.F., Rushdi, M.A., Yassine, I.A.: Feature and decision-level fusion for schizophrenia detection based on resting-state fMRI data. PLoS ONE 17(5), e0265300 (2022). https://doi.org/10.1371/journal.pone.0265300
2. Tang, Y., Wang, L., Cao, F., Tan, L.: Identify schizophrenia using resting-state functional connectivity: an exploratory research and analysis. Biomed. Eng. Online 11, 1–16 (2012). https://doi.org/10.1186/1475-925X-11-50
3. Yu, Y., Shen, H., Zhang, H., Zeng, L.-L., Xue, Z., Hu, D.: Functional connectivity-based signatures of schizophrenia revealed by multiclass pattern analysis of resting-state fMRI from schizophrenic patients and their healthy siblings. Biomed. Eng. Online 12(1), 1–13 (2013). https://doi.org/10.1186/1475-925X-12-10
4. Guo, W., et al.: Decreased regional activity of default-mode network in unaffected siblings of schizophrenia patients at rest. Eur. Neuropsychopharmacol. 24(4), 545–552 (2014). https://doi.org/10.1016/j.euroneuro.2014.01.004
5. Gao, S., et al.: Enhanced prefrontal regional homogeneity and its correlations with cognitive dysfunction/psychopathology in patients with first-diagnosed and drug-naive schizophrenia. Front. Psych. 11, 580570 (2020). https://doi.org/10.3389/fpsyt.2020.580570
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