Predictive modeling of treatment resistant depression using data from STAR*D and an independent clinical study.
Identification of risk factors of treatment resistance may be useful to guide treatment selection, avoid inefficient trial-and-error, and improve major depressive disorder (MDD) care. We extended the work in predictive modeling of treatment resistant depression (TRD) via partition of the data from t...
Saved in:
Similar Items
-
Identifying depression subtypes and investigating their consistency and transitions in a 1-year cohort analysis.
by: Carolin Oetzmann, et al.
Published: (2025-01-01) -
Assessing seasonal and weather effects on depression and physical activity using mobile health data
by: Yuezhou Zhang, et al.
Published: (2025-04-01) -
Correction: Replication of machine learning methods to predict treatment outcome with antidepressant medications in patients with major depressive disorder from STAR*D and CAN-BIND-1.
by: John-Jose Nunez, et al.
Published: (2024-01-01) -
Vitamin D deficiency, fatigue, and persistent cough as independent predictors of depressive symptoms in sarcoidosis patients
by: Gvozdenovic Branislav S., et al.
Published: (2025-01-01) -
Handgrip Strength, Depression, Dementia, Cognitive Function, and Their Predictive Effect on Functional Independence in Older Adults
by: Juan Antonio Campos-Gutiérrez, et al.
Published: (2025-06-01)