Linling Jiang
Biographic Data
| ID | 7960233 |
|---|---|
| NAME | Linling Jiang |
| GIVEN NAMES | Linling |
| FAMILY NAME | Jiang |
| SIGNATURE | JIANG L |
| AFFILIATIONS | Kunming Medical University |
| VERIFIED | No |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Integrated transcriptomic and machine learning analysis reveals novel diagnostic biomarkers for adolescent major depressive disorder
This study delineates a systemic molecular landscape of adolescent MDD defined by the coexistence of hypoxic compensation and neurotrophic/remodeling failure. The identified three-gene biosignature (SLC4A1, IGF1, MMP9) offers a promising, objective tool for the early diagnosis of adolescent depression, highlighting the immune-metabolic interface as a critical avenue for future precision medicine
Network analysis in depressed adolescents with suicidal ideation: The role of depression, anxiety, and childhood abuse
Emotional abuse and bridge symptoms (e.g., fatigue and uncontrolled worry) are critical intervention targets for suicide-prevention interventions. A multimodal approach integrating cognitive-behavioral therapy for core symptom management, family-based interventions to address attachment disruptions, and policy initiatives to reduce childhood abuse is recommended
Prevalence of depressive disorders and treatment in China: A cross-sectional epidemiological study
Support Vector Machine Classification of Obsessive-Compulsive Disorder Based on Whole-Brain Volumetry and Diffusion Tensor Imaging
Magnetic resonance imaging (MRI) methods have been used to detect cerebral anatomical distinction between obsessive-compulsive disorder (OCD) patients and healthy controls (HC). Machine learning approach allows for the possibility of discriminating patients on the individual level. However, few studies have used this automatic technique based on multiple modalities to identify potential biomarkers of OCD. High-resolution structural MRI and diffus…
No prominent works on this page.
Support Vector Machine Classification of Obsessive-Compulsive Disorder Based on Whole-Brain Volumetry and Diffusion Tensor Imaging
Magnetic resonance imaging (MRI) methods have been used to detect cerebral anatomical distinction between obsessive-compulsive disorder (OCD) patients and healthy controls (HC). Machine learning approach allows for the possibility of discriminating patients on the individual level. However, few studies have used this automatic technique based on multiple modalities to identify potential biomarkers of OCD. High-resolution structural MRI and diffus…
Prevalence of depressive disorders and treatment in China: A cross-sectional epidemiological study
Network analysis in depressed adolescents with suicidal ideation: The role of depression, anxiety, and childhood abuse
Emotional abuse and bridge symptoms (e.g., fatigue and uncontrolled worry) are critical intervention targets for suicide-prevention interventions. A multimodal approach integrating cognitive-behavioral therapy for core symptom management, family-based interventions to address attachment disruptions, and policy initiatives to reduce childhood abuse is recommended
Integrated transcriptomic and machine learning analysis reveals novel diagnostic biomarkers for adolescent major depressive disorder
This study delineates a systemic molecular landscape of adolescent MDD defined by the coexistence of hypoxic compensation and neurotrophic/remodeling failure. The identified three-gene biosignature (SLC4A1, IGF1, MMP9) offers a promising, objective tool for the early diagnosis of adolescent depression, highlighting the immune-metabolic interface as a critical avenue for future precision medicine
Medicine (3 works) · Major depressive disorder (2 works) · Psychiatry (2 works) · Psychology (2 works) · Treatment of Major Depression (2 works) · Advanced Neuroimaging Techniques and Applications (1 works) · Anxiety (1 works) · Artificial Intelligence (1 works) · Biomarker (1 works) · Cardiac Health and Mental Health (1 works)