Focal Interest
Focal Interest

Major depressive disorder

  1. Facial-video heart rate variability modestly distinguished depressive symptoms
    Stacking ensemble classifier combines facial video-derived heart rate variability with demographics to screen depression with moderate discrimination. AUROC 0.64 achieved across 1453 individuals.
  2. Adverse childhood experiences were linked to higher risk of treatment-resistant depression
    Cohort study demonstrating association between adverse childhood experiences and treatment-resistant depression, independent of familial confounding factors.
  3. The role of psychotherapy with a Quranic approach to improving women's depression: A Case Study
    Single-case study examining Quranic-based psychotherapy for major depressive disorder in a 60-year-old woman, showing sustained symptom reduction through follow-up.
  4. Predictors of emergent depression included stress, coping, and social strain
    Longitudinal predictive modeling identifies psychosocial and demographic risk factors for emergent major depressive disorder using machine learning explainability methods.
  5. Reasoning-based LLMs may predict antidepressant response
    Study evaluates reasoning-based large language models for predicting 12-week remission in depressive disorder patients undergoing antidepressant monotherapy.