Shouliang Qi
Biographic Data
| ID | 7958531 |
|---|---|
| NAME | Shouliang Qi |
| GIVEN NAMES | Shouliang |
| FAMILY NAME | Qi |
| SIGNATURE | QI S |
| AFFILIATIONS | Northeastern University |
| ORCID | 0000-0003-0977-1939 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Predicting depression by using a novel deep learning model and video-audio-text multimodal data
These results underscore the robustness and precision of the IMDD-Net, highlighting the importance of integrating local and global features across multiple modalities for accurate depression prediction
Aberrant degree centrality of functional brain networks in subclinical depression and major depressive disorder
Altered DC in the STG, MTG, IPL, and MFG were identified in depression groups. The DC values of these altered regions and their combinations presented good discriminative ability between HC, SD, and MDD. These findings could help to find effective biomarkers and reveal the potential mechanisms of depression
Connectome-Based Biomarkers Predict Subclinical Depression and Identify Abnormal Brain Connections With the Lateral Habenula and Thalamus
Subclinical depression (SD) has been considered as the precursor to major depressive disorder. Accurate prediction of SD and identification of its etiological origin are urgent. Bursts within the lateral habenula (LHb) drive depression in rats, but whether dysfunctional LHb is associated with SD in human is unknown. Here we develop connectome-based biomarkers which predict SD and identify dysfunctional brain regions and connections. T1 weighted i…
No prominent works on this page.
Connectome-Based Biomarkers Predict Subclinical Depression and Identify Abnormal Brain Connections With the Lateral Habenula and Thalamus
Subclinical depression (SD) has been considered as the precursor to major depressive disorder. Accurate prediction of SD and identification of its etiological origin are urgent. Bursts within the lateral habenula (LHb) drive depression in rats, but whether dysfunctional LHb is associated with SD in human is unknown. Here we develop connectome-based biomarkers which predict SD and identify dysfunctional brain regions and connections. T1 weighted i…
Aberrant degree centrality of functional brain networks in subclinical depression and major depressive disorder
Altered DC in the STG, MTG, IPL, and MFG were identified in depression groups. The DC values of these altered regions and their combinations presented good discriminative ability between HC, SD, and MDD. These findings could help to find effective biomarkers and reveal the potential mechanisms of depression
Predicting depression by using a novel deep learning model and video-audio-text multimodal data
These results underscore the robustness and precision of the IMDD-Net, highlighting the importance of integrating local and global features across multiple modalities for accurate depression prediction
Depression (economics (2 works) · Functional Brain Connectivity Studies (2 works) · Internal Medicine (2 works) · Major depressive disorder (2 works) · Medicine (2 works) · Neuroscience (2 works) · Psychology (2 works) · Receiver operating characteristic (2 works) · Resting state fMRI (2 works) · Advanced MRI Techniques and Applications (1 works)