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. Childhood adversity linked to higher treatment-resistant depression risk
    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. Predictive modeling identified later emergent depression risk
    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.